From 55cb9cb143f815019edf03f47a0b5d6b15c64ebc Mon Sep 17 00:00:00 2001
From: gitea_admin <gitea@local.domain>
Date: Mon, 20 Jul 2026 09:47:45 +0000
Subject: [PATCH] Upload files to "intelliarcs/__intelliarcs"

---
 intelliarcs/__intelliarcs/exceptions-360.json | 829 ++++++++++++++++++
 intelliarcs/__intelliarcs/experience-360.json | 829 ++++++++++++++++++
 intelliarcs/__intelliarcs/meta.json           |  26 +
 3 files changed, 1684 insertions(+)
 create mode 100644 intelliarcs/__intelliarcs/exceptions-360.json
 create mode 100644 intelliarcs/__intelliarcs/experience-360.json
 create mode 100644 intelliarcs/__intelliarcs/meta.json

diff --git a/intelliarcs/__intelliarcs/exceptions-360.json b/intelliarcs/__intelliarcs/exceptions-360.json
new file mode 100644
index 0000000..220dc9d
--- /dev/null
+++ b/intelliarcs/__intelliarcs/exceptions-360.json
@@ -0,0 +1,829 @@
+{
+  "id": "experience-360",
+  "name": "Experience 360",
+  "description": "Revolutionize customer engagement with Experience360 a powerful AI-driven platform designed for both agents and customers.",
+  "status": "87% Complete",
+  "statusType": "progress",
+  "tabs": [
+    {
+      "name": "Overview",
+      "description": "Revolutionize customer engagement with Experience360 a powerful AI-driven platform designed for both agents and customers.",
+      "goals": ["Enhance the profitability of the target product by 6%"],
+      "objective": "Leverage a self-directed Multi Agent System to achieve a 6% increase in target product profitability",
+      "roles": [
+        {
+          "name": "Product Manager",
+          "description": ""
+        }
+      ],
+      "benefits": [
+        "Deliver proactive insights to help product managers anticipate market trends and customer needs",
+        "Enable data-driven decision-making that directly supports revenue growth and strategic product development",
+        "Identify opportunities to boost profitability through optimized pricing, feature prioritization, and resource allocation",
+        "Strengthen customer loyalty by aligning product decisions with user behavior and engagement data"
+      ]
+    },
+    {
+      "name": "Bill of Materials",
+      "description": "Bill of Materials - Visual representation of Multi-Agent System architecture and component relationships.",
+      "data": {
+        "orchestrator": [
+          {
+            "id": "orchestrator-1",
+            "name": "Enrich 360 Lyza Agent",
+            "type": "ORCHESTRATOR_AGENT",
+            "version": "V 1.2",
+            "metadata": {},
+            "upstreamConnections": [],
+            "downstreamConnections": [
+              "agent-churn",
+              "agent-recommendation",
+              "agent-sentiment",
+              "agent-chart-generation",
+              "agent-competitor-insights",
+              "agent-price-optimization",
+              "agent-product-intelligence",
+              "agent-usage-analyzer",
+              "agent-market-insights",
+              "agent-similar-accounts",
+              "agent-epm"
+            ]
+          }
+        ],
+        "agents": [
+          {
+            "id": "agent-churn",
+            "name": "Churn Management Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Manages customer churn prevention"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": ["model-churn", "model-churn-mitigation"]
+          },
+          {
+            "id": "agent-recommendation",
+            "name": "Product Recommendation Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Suggests products by customer"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": ["model-recommendation"]
+          },
+          {
+            "id": "agent-sentiment",
+            "name": "Customer Sentiment Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Analyzes customer sentiment and feedback"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": ["model-sentiment"]
+          },
+          {
+            "id": "agent-chart-generation",
+            "name": "Chart Generation Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Creates charts and graphs from data"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-competitor-insights",
+            "name": "Competitor Insights Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights on product and market"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-price-optimization",
+            "name": "Price Optimization Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for customer"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-product-intelligence",
+            "name": "Product Intelligence Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for product"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-usage-analyzer",
+            "name": "Usage Analyzer Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for user"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-market-insights",
+            "name": "Market Insights Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for industry and market"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-similar-accounts",
+            "name": "Similar Accounts",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Finds accounts for users"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-epm",
+            "name": "EPM Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers data analytics and digital"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          }
+        ],
+        "models": [
+          {
+            "id": "model-churn",
+            "name": "Likelihood of Churn Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": ["agent-churn"],
+            "downstreamConnections": ["fs-churn", "is-churn"]
+          },
+          {
+            "id": "model-recommendation",
+            "name": "Product Recommendation Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 12,
+              "size": "2 GB"
+            },
+            "upstreamConnections": ["agent-recommendation"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-sentiment",
+            "name": "Sentiment Analysis Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 6,
+              "size": "1 GB"
+            },
+            "upstreamConnections": ["agent-sentiment"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-competitor-insights",
+            "name": "Competitor Insights Agent",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-price-optimization",
+            "name": "Price Optimization Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-product-intelligence",
+            "name": "Product Intelligence Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-usage-classification",
+            "name": "Usage Classification Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-similar-accounts",
+            "name": "Similar Accounts Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-usage-forecasting",
+            "name": "Usage Forecasting Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-churn-mitigation",
+            "name": "Churn Mitigation Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": ["agent-churn"],
+            "downstreamConnections": ["fs-churn", "is-churn"]
+          }
+        ],
+        "tools": [
+          {
+            "id": "tool-batch",
+            "name": "Batch job",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 4
+            },
+            "upstreamConnections": ["model-churn"],
+            "downstreamConnections": ["fs-churn"]
+          },
+          {
+            "id": "tool-stream",
+            "name": "Stream",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 2
+            },
+            "upstreamConnections": ["model-churn"],
+            "downstreamConnections": ["is-churn"]
+          },
+          {
+            "id": "tool-chart-generation",
+            "name": "Chart Generation Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 4
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-news-mcf",
+            "name": "News MCF tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-weather-mcf",
+            "name": "Weather MCF tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 3
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-web-search",
+            "name": "Web Search Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-epm-text-to-sql",
+            "name": "EPM Text-to-SQL Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 1
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-epm-mcf",
+            "name": "EPM MCF Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 1
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ],
+        "dataEntities": [
+          {
+            "id": "entity-customer",
+            "name": "Customer",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 15
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          },
+          {
+            "id": "entity-invoices",
+            "name": "Invoices",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 12
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          },
+          {
+            "id": "entity-transactions",
+            "name": "Transactions",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 18
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          },
+          {
+            "id": "entity-products",
+            "name": "Products",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          }
+        ],
+        "featureStores": [
+          {
+            "id": "fs-churn",
+            "name": "Churn feature Store",
+            "type": "FEATURE_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8,
+              "workflows": 1
+            },
+            "upstreamConnections": ["model-churn", "model-churn-mitigation"],
+            "downstreamConnections": [
+              "entity-customer",
+              "entity-invoices",
+              "entity-transactions",
+              "entity-products"
+            ]
+          },
+          {
+            "id": "fs-product-recommendation",
+            "name": "Product Recommendation Feature Store",
+            "type": "FEATURE_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 10,
+              "workflows": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ],
+        "insightStores": [
+          {
+            "id": "is-churn",
+            "name": "Churn Insights Store",
+            "type": "INSIGHTS_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8,
+              "workflows": 1
+            },
+            "upstreamConnections": ["model-churn", "model-churn-mitigation"],
+            "downstreamConnections": [
+              "entity-customer",
+              "entity-invoices",
+              "entity-transactions",
+              "entity-products"
+            ]
+          },
+          {
+            "id": "insight-churn-data",
+            "name": "Churn Insights Data",
+            "type": "INSIGHTS_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 6,
+              "workflows": 1
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "insight-product-recommendation",
+            "name": "Product Recommendation Insights data",
+            "type": "INSIGHTS_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8,
+              "workflows": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ],
+        "dataSources": [
+          {
+            "id": "ds-hogan",
+            "name": "Hogan Banking Core",
+            "type": "DATA_SOURCE",
+            "version": "V 1.2",
+            "metadata": {
+              "files": 12,
+              "fields": 45
+            },
+            "upstreamConnections": [
+              "entity-customer",
+              "entity-invoices",
+              "entity-transactions",
+              "entity-products"
+            ],
+            "downstreamConnections": []
+          },
+          {
+            "id": "ds-salesforce",
+            "name": "Salesforce CRM",
+            "type": "DATA_SOURCE",
+            "version": "V 1.2",
+            "metadata": {
+              "files": 8,
+              "fields": 32
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ]
+      }
+    },
+    {
+      "name": "LYZA",
+      "description": "Multi-Agent System (MAS) designed to empower users to create AI application",
+      "system_prompt": "# 🧠 System Prompt: Multi-Agent System for Profitability Optimization\n\n## 🎯 System Objective\n**Leverage a self-directed Multi-Agent System (MAS) to enhance the profitability of the target product by 6%.**\n\n## 🧑‍💼 Primary User Persona\n- **Role**: Product Manager  \n- **Goals**:\n  - Deliver proactive insights on market trends and customer needs.\n  - Enable data-driven decision-making for revenue and strategic development.\n  - Identify opportunities through pricing, feature prioritization, and resource allocation.\n  - Align product direction with user behavior to boost loyalty and retention.\n\n\n## 🧠 System Architecture & Agents\n\n### 1. Market Trends Agent\n- Scrapes and synthesizes industry news, competitor moves, and consumer behavior.\n- Forecasts market demand shifts.\n- **Outputs**: Trend dashboards, early warnings, opportunity maps.\n\n### 2. Customer Intelligence Agent\n- Analyzes interaction logs, reviews, NPS, and churn indicators.\n- Segments users by behavior, sentiment, and value.\n- **Outputs**: Loyalty drivers, friction points, feature adoption trends.\n\n### 3. Pricing & Profitability Agent\n- Simulates pricing and bundling strategies using internal and competitive data.\n- Optimizes for revenue per user, margin, and LTV/CAC.\n- **Outputs**: Dynamic pricing recs, test strategies.\n\n### 4. Feature Prioritization Agent\n- Evaluates feature ROI using A/B test data, analytics, and requests.\n- Prioritizes by impact, feasibility, alignment.\n- **Outputs**: Roadmap priorities with ROI scoring.\n\n### 5. Strategic Alignment Agent\n- Maps recommendations to business OKRs and product KPIs.\n- Aligns output with executive vision.\n- **Outputs**: OKR scorecards, strategic impact alerts.\n\n---\n\n## 📊 Key Performance Indicators (KPIs)\n\n| KPI | Target | Measured By |\n|-----|--------|-------------|\n| **Product Profitability Uplift** | +6% | (Revenue - COGS)/Revenue |\n| **Customer Lifetime Value (LTV)** | +10% | Avg. revenue per customer lifecycle |\n| **Churn Rate** | -15% | % of users leaving per month |\n| **Feature Adoption Rate** | +20% | % of users using new features |\n| **ARPU (Avg. Revenue/User)** | +5% | Revenue ÷ Active Users |\n| **Time-to-Insight** | -30% | Data → Action latency |\n| **Insight Utilization Rate** | +40% | % of insights influencing actions |\n\n---\n\n## 🔍 Sample Insights\n\n### Market-Driven\n- \"Gen Z shift to mobile-first productivity tools = 12% drop in desktop use.\"\n- \"Competitor pricing shift caused 8% churn in overlapping user base.\"\n\n### Customer Behavior\n- \"Low onboarding completion = 3x higher churn.\"\n- \"Power users love Feature X; UI promotion could lift adoption by 15%.\"\n\n### Profitability Levers\n- \"Feature A + B bundle → +9% profit in Tier 2 users.\"\n- \"Proactive support bot reduces per-user cost → +2% margin.\"\n\n### Feature ROI\n- \"Feature C = $480K/year projected uplift.\"\n- \"Feature B = high dev cost, <1% revenue impact — deprioritize.\"\n\n### Strategic Forecasts\n- \"Entering Vertical Y in 6 months → +15% LTV based on market signals.\"\n\n---\n\n## 🧩 Data Assets Utilized\n\n- **Product Analytics**: Mixpanel, Amplitude, GA\n- **CRM & Sales**: Salesforce, HubSpot\n- **Customer Feedback**: NPS, Zendesk, UserVoice\n- **Behavioral Tools**: Segment, FullStory, Heap\n- **Financial Systems**: ERP, P&L Data\n- **Competitive Data**: SimilarWeb, AppAnnie\n- **Custom Data**: Proprietary usage and support metrics\n\n---\n\n## 🔄 Decision Loop & Agent Autonomy\n\n- **Central Coordination Hub** integrates agent output.\n- Resolves conflicts, ranks ideas by profitability impact.\n- Proposes action plans with data traceability.\n- **Escalation** to Product Manager for high-impact decisions.\n\n---\n\n## 🔐 Governance, Control & Guardrails\n\n- **Human-in-the-loop** for major product/pricing decisions.\n- **Bias detection** on predictive models.\n- **Explainability** for all recommendations (with data trace).\n- **Audit logs** for decision transparency.\n\n---\n\n## 📅 Weekly Outputs\n\n- **Executive Summary**: Top 5 profitability drivers.\n- **Feature ROI Tracker**: Updated roadmap impacts.\n- **Customer Health Report**: Segments at risk/opportunity.\n- **Pricing Simulations**: Scenarios with projected profit impact.\n- **Agent Confidence Scores**: Trust levels per suggestion.\n\n---\n\n## ✅ Summary\n\nA self-directed MAS empowers the Product Manager to:\n- Predict market trends.\n- Act on user needs.\n- Make smarter roadmap and pricing decisions.\n- Achieve a sustained 6%+ profitability uplift with explainable, data-backed insights.",
+      "mas": [
+        {
+          "name": "Enrich360 Offline Process",
+          "description": "Batch enrichment engine designed for large-scale data processing, ensuring accuracy and consistency at scale",
+          "updated_at": "2025-06-04T05:54:09+00:00",
+          "tags": ["assistants", "agents", "MAS"],
+          "id": "532ed470-b97d-4171-8121-07fbff800728",
+          "folder_id": "a2956334-e842-44ac-96aa-7190bfa5396c"
+        },
+        {
+          "name": "Enrich360 Interactive",
+          "description": "Empowers product managers with real-time, user-driven insights to make faster, data-backed decisions",
+          "updated_at": "2025-06-04T05:54:20+00:00",
+          "tags": ["assistants", "agents", "MAS"],
+          "id": "f8d4f2f9-5285-45b0-8eda-cd0043e230e3",
+          "folder_id": "a2956334-e842-44ac-96aa-7190bfa5396c"
+        }
+      ]
+    },
+    {
+      "name": "Presentations",
+      "description": "Visual insights and demos showcasing Experience 360 capabilities.",
+      "deployed_urls": [
+        {
+          "url": "/intarc/dashboard",
+          "description": "This is where the Enrich360 UI is deployed. Click to open the live instance."
+        }
+      ]
+    },
+    {
+      "name": "Deployment",
+      "description": "Tools and settings to launch, monitor, and manage AI solution in real-time environments.",
+      "configuration": "Kubernetes",
+      "version": "V 1.2",
+      "replicas": {
+        "model": 3,
+        "agent": 2,
+        "logging": 1,
+        "monitoring": 1
+      },
+      "yaml": "# -----------------------------------------------------\n# enrich360 AI Model Deployment\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-model\n  labels:\n    app: enrich360\n    component: model\nspec:\n  replicas: 3\n  selector:\n    matchLabels:\n      app: enrich360\n      component: model\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: model\n    spec:\n      containers:\n      - name: model-server\n        image: enrich360/model-server:latest\n        ports:\n        - containerPort: 8000\n        env:\n        - name: MODEL_PATH\n          value: /models/classifier-v2.pth\n        - name: LOG_LEVEL\n          value: info\n        volumeMounts:\n        - name: model-storage\n          mountPath: /models\n      volumes:\n      - name: model-storage\n        persistentVolumeClaim:\n          claimName: enrich360-model-pvc\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-model-service\nspec:\n  selector:\n    app: enrich360\n    component: model\n  ports:\n  - port: 80\n    targetPort: 8000\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# enrich360 Agent (AI Decision-Maker)\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-agent\n  labels:\n    app: enrich360\n    component: agent\nspec:\n  replicas: 2\n  selector:\n    matchLabels:\n      app: enrich360\n      component: agent\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: agent\n    spec:\n      containers:\n      - name: agent-service\n        image: enrich360/agent:stable\n        ports:\n        - containerPort: 8500\n        env:\n        - name: MODEL_API_URL\n          value: http://enrich360-model-service/predict\n        - name: AGENT_MODE\n          value: production\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-agent-service\nspec:\n  selector:\n    app: enrich360\n    component: agent\n  ports:\n  - port: 85\n    targetPort: 8500\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# enrich360 Logging Service (e.g., Fluentd, Loki)\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-logging\n  labels:\n    app: enrich360\n    component: logging\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: enrich360\n      component: logging\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: logging\n    spec:\n      containers:\n      - name: logger\n        image: enrich360/logging:latest\n        ports:\n        - containerPort: 24224\n        volumeMounts:\n        - name: log-storage\n          mountPath: /var/log/enrich360\n      volumes:\n      - name: log-storage\n        emptyDir: {}\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-logging-service\nspec:\n  selector:\n    app: enrich360\n    component: logging\n  ports:\n  - port: 24224\n    targetPort: 24224\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# enrich360 Monitoring Dashboard (e.g., Prometheus + Grafana)\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-monitoring\n  labels:\n    app: enrich360\n    component: monitoring\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: enrich360\n      component: monitoring\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: monitoring\n    spec:\n      containers:\n      - name: prometheus\n        image: prom/prometheus:latest\n        ports:\n        - containerPort: 9090\n        volumeMounts:\n        - name: prom-config\n          mountPath: /etc/prometheus\n      volumes:\n      - name: prom-config\n        configMap:\n          name: enrich360-prometheus-config\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-monitoring-service\nspec:\n  selector:\n    app: enrich360\n    component: monitoring\n  ports:\n  - port: 90\n    targetPort: 9090\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# Persistent Volume Claim for Model Storage\n# -----------------------------------------------------\napiVersion: v1\nkind: PersistentVolumeClaim\nmetadata:\n  name: enrich360-model-pvc\nspec:\n  accessModes:\n    - ReadWriteOnce\n  resources:\n    requests:\n      storage: 2Gi\n\n---\n# -----------------------------------------------------\n# ConfigMap for Prometheus Configuration (Example)\n# -----------------------------------------------------\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: enrich360-prometheus-config\ndata:\n  prometheus.yml: |\n    global:\n      scrape_interval: 15s\n    scrape_configs:\n      - job_name: 'enrich360'\n        static_configs:\n          - targets: ['enrich360-model-service:80', 'enrich360-agent-service:85']",
+      "services": [
+        "enrich360-model-service",
+        "enrich360-agent-service",
+        "enrich360-logging-service",
+        "enrich360-monitoring-service"
+      ],
+      "endpoints": [
+        {
+          "name": "Get Revenue Optimizer",
+          "description": "AI Agent",
+          "url": "/ai-agent",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Alerts",
+          "description": "Dataset",
+          "url": "/dataset",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Product Metrics",
+          "description": "Dashboard",
+          "url": "/dashboard",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Churn Management Insights",
+          "description": "ML Model",
+          "url": "/ml-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Prospect Identification Insights",
+          "description": "Model",
+          "url": "/model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Market Insights",
+          "description": "Gen AI Model",
+          "url": "/gen-ai-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Customer Sentiment",
+          "description": "ML Model",
+          "url": "/ml-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Competitor Watch",
+          "description": "Gen AI Model",
+          "url": "/gen-ai-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Suggested Questions",
+          "description": "Gen AI Model",
+          "url": "/gen-ai-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "LYZA Enrich360 MAS",
+          "description": "Enrich360 MAS",
+          "url": "/enrich360-mas",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Authentication Service",
+          "description": "Handles user authentication and authorization",
+          "url": "/auth",
+          "version": "1.0.0",
+          "status": "Active"
+        }
+      ]
+    },
+    {
+      "name": "KPI",
+      "description": "Dashboard tracking key performance indicators to evaluate AI application effectiveness.",
+      "business": [
+        {
+          "name": "Revenue",
+          "description": "Overall Revenue Targets",
+          "id": "kpi-business-001",
+          "url": "/kpis/revenue",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-4%",
+          "target": "$100.3M"
+        },
+        {
+          "name": "Profitability",
+          "description": "Product Profitability",
+          "id": "kpi-business-002",
+          "url": "/kpis/profitability",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-6%",
+          "target": "45%"
+        },
+        {
+          "name": "Cost to Serve",
+          "description": "Cost to Serve my product",
+          "id": "kpi-business-003",
+          "url": "/kpis/cost-to-serve",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-2.5%",
+          "target": "$18.2M"
+        },
+        {
+          "name": "Churn Rate",
+          "description": "Target churn rate of customers",
+          "id": "kpi-business-004",
+          "url": "/kpis/churn-rate",
+          "version": "V 1.2",
+          "status": "Improving",
+          "trend": "+2%",
+          "target": "12.5%"
+        },
+        {
+          "name": "Product Usage",
+          "description": "Transactions",
+          "id": "kpi-business-005",
+          "url": "/kpis/product-usage",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-$2.35M",
+          "target": "24.5M"
+        },
+        {
+          "name": "Waivers",
+          "description": "Product Waivers",
+          "id": "kpi-business-006",
+          "url": "/kpis/waivers",
+          "version": "V 1.2",
+          "status": "Improving",
+          "trend": "+11.3%",
+          "target": "$9.6M"
+        }
+      ],
+      "technical": [
+        {
+          "name": "Processing Efficiency",
+          "description": "Current processing efficiency rate",
+          "id": "kpi-technical-001",
+          "url": "/kpis/processing-efficiency",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "98%",
+          "target": "95%",
+          "trend": "+3% from last month"
+        },
+        {
+          "name": "Error Rate",
+          "description": "System error occurrence rate",
+          "id": "kpi-technical-002",
+          "url": "/kpis/error-rate",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "1.2%",
+          "target": "<2%",
+          "trend": "-0.5% from last month"
+        },
+        {
+          "name": "Response Time",
+          "description": "Average API response time",
+          "id": "kpi-technical-003",
+          "url": "/kpis/response-time",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "150ms",
+          "target": "<200ms",
+          "trend": "-50ms from last month"
+        },
+        {
+          "name": "Uptime",
+          "description": "System availability percentage",
+          "id": "kpi-technical-004",
+          "url": "/kpis/uptime",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "99.9%",
+          "target": "99.9%",
+          "trend": "+0.1% from last month"
+        },
+        {
+          "name": "Data Accuracy",
+          "description": "Data validation success rate",
+          "id": "kpi-technical-005",
+          "url": "/kpis/data-accuracy",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "99.5%",
+          "target": "99%",
+          "trend": "+0.5% from last month"
+        }
+      ]
+    },
+    {
+      "name": "Reports",
+      "description": "Generated summaries and logs detailing system performance and agent behavior.",
+      "reports": [
+        {
+          "name": "Performance Report",
+          "description": "Detailed analysis of system performance metrics",
+          "id": "report-performance-001",
+          "url": "/reports/performance",
+          "version": "V 1.2",
+          "status": "Active",
+          "last_updated": "Today"
+        },
+        {
+          "name": "Usage Analytics",
+          "description": "User engagement and system utilization statistics",
+          "id": "report-usage-analytics-001",
+          "url": "/reports/usage-analytics",
+          "version": "V 1.2",
+          "status": "Active",
+          "last_updated": "Today"
+        },
+        {
+          "name": "Error Log Report",
+          "description": "Comprehensive error tracking and resolution status",
+          "id": "report-error-log-001",
+          "url": "/reports/error-logs",
+          "version": "V 1.2",
+          "status": "Active",
+          "last_updated": "Today"
+        }
+      ]
+    }
+  ]
+}
diff --git a/intelliarcs/__intelliarcs/experience-360.json b/intelliarcs/__intelliarcs/experience-360.json
new file mode 100644
index 0000000..220dc9d
--- /dev/null
+++ b/intelliarcs/__intelliarcs/experience-360.json
@@ -0,0 +1,829 @@
+{
+  "id": "experience-360",
+  "name": "Experience 360",
+  "description": "Revolutionize customer engagement with Experience360 a powerful AI-driven platform designed for both agents and customers.",
+  "status": "87% Complete",
+  "statusType": "progress",
+  "tabs": [
+    {
+      "name": "Overview",
+      "description": "Revolutionize customer engagement with Experience360 a powerful AI-driven platform designed for both agents and customers.",
+      "goals": ["Enhance the profitability of the target product by 6%"],
+      "objective": "Leverage a self-directed Multi Agent System to achieve a 6% increase in target product profitability",
+      "roles": [
+        {
+          "name": "Product Manager",
+          "description": ""
+        }
+      ],
+      "benefits": [
+        "Deliver proactive insights to help product managers anticipate market trends and customer needs",
+        "Enable data-driven decision-making that directly supports revenue growth and strategic product development",
+        "Identify opportunities to boost profitability through optimized pricing, feature prioritization, and resource allocation",
+        "Strengthen customer loyalty by aligning product decisions with user behavior and engagement data"
+      ]
+    },
+    {
+      "name": "Bill of Materials",
+      "description": "Bill of Materials - Visual representation of Multi-Agent System architecture and component relationships.",
+      "data": {
+        "orchestrator": [
+          {
+            "id": "orchestrator-1",
+            "name": "Enrich 360 Lyza Agent",
+            "type": "ORCHESTRATOR_AGENT",
+            "version": "V 1.2",
+            "metadata": {},
+            "upstreamConnections": [],
+            "downstreamConnections": [
+              "agent-churn",
+              "agent-recommendation",
+              "agent-sentiment",
+              "agent-chart-generation",
+              "agent-competitor-insights",
+              "agent-price-optimization",
+              "agent-product-intelligence",
+              "agent-usage-analyzer",
+              "agent-market-insights",
+              "agent-similar-accounts",
+              "agent-epm"
+            ]
+          }
+        ],
+        "agents": [
+          {
+            "id": "agent-churn",
+            "name": "Churn Management Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Manages customer churn prevention"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": ["model-churn", "model-churn-mitigation"]
+          },
+          {
+            "id": "agent-recommendation",
+            "name": "Product Recommendation Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Suggests products by customer"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": ["model-recommendation"]
+          },
+          {
+            "id": "agent-sentiment",
+            "name": "Customer Sentiment Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Analyzes customer sentiment and feedback"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": ["model-sentiment"]
+          },
+          {
+            "id": "agent-chart-generation",
+            "name": "Chart Generation Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Creates charts and graphs from data"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-competitor-insights",
+            "name": "Competitor Insights Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights on product and market"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-price-optimization",
+            "name": "Price Optimization Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for customer"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-product-intelligence",
+            "name": "Product Intelligence Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for product"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-usage-analyzer",
+            "name": "Usage Analyzer Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for user"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-market-insights",
+            "name": "Market Insights Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers insights for industry and market"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-similar-accounts",
+            "name": "Similar Accounts",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Finds accounts for users"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "agent-epm",
+            "name": "EPM Agent",
+            "type": "AGENT",
+            "version": "V 1.2",
+            "metadata": {
+              "description": "Offers data analytics and digital"
+            },
+            "upstreamConnections": ["orchestrator-1"],
+            "downstreamConnections": []
+          }
+        ],
+        "models": [
+          {
+            "id": "model-churn",
+            "name": "Likelihood of Churn Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": ["agent-churn"],
+            "downstreamConnections": ["fs-churn", "is-churn"]
+          },
+          {
+            "id": "model-recommendation",
+            "name": "Product Recommendation Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 12,
+              "size": "2 GB"
+            },
+            "upstreamConnections": ["agent-recommendation"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-sentiment",
+            "name": "Sentiment Analysis Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 6,
+              "size": "1 GB"
+            },
+            "upstreamConnections": ["agent-sentiment"],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-competitor-insights",
+            "name": "Competitor Insights Agent",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-price-optimization",
+            "name": "Price Optimization Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-product-intelligence",
+            "name": "Product Intelligence Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-usage-classification",
+            "name": "Usage Classification Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-similar-accounts",
+            "name": "Similar Accounts Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-usage-forecasting",
+            "name": "Usage Forecasting Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "model-churn-mitigation",
+            "name": "Churn Mitigation Model",
+            "type": "MODEL",
+            "version": "V 1.2",
+            "metadata": {
+              "parameters": 8,
+              "size": "1 GB"
+            },
+            "upstreamConnections": ["agent-churn"],
+            "downstreamConnections": ["fs-churn", "is-churn"]
+          }
+        ],
+        "tools": [
+          {
+            "id": "tool-batch",
+            "name": "Batch job",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 4
+            },
+            "upstreamConnections": ["model-churn"],
+            "downstreamConnections": ["fs-churn"]
+          },
+          {
+            "id": "tool-stream",
+            "name": "Stream",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 2
+            },
+            "upstreamConnections": ["model-churn"],
+            "downstreamConnections": ["is-churn"]
+          },
+          {
+            "id": "tool-chart-generation",
+            "name": "Chart Generation Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 4
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-news-mcf",
+            "name": "News MCF tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-weather-mcf",
+            "name": "Weather MCF tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 3
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-web-search",
+            "name": "Web Search Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-epm-text-to-sql",
+            "name": "EPM Text-to-SQL Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 1
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "tool-epm-mcf",
+            "name": "EPM MCF Tool",
+            "type": "TOOL",
+            "version": "V 1.2",
+            "metadata": {
+              "interfaces": 1
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ],
+        "dataEntities": [
+          {
+            "id": "entity-customer",
+            "name": "Customer",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 15
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          },
+          {
+            "id": "entity-invoices",
+            "name": "Invoices",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 12
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          },
+          {
+            "id": "entity-transactions",
+            "name": "Transactions",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 18
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          },
+          {
+            "id": "entity-products",
+            "name": "Products",
+            "type": "DATA_ENTITY",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8
+            },
+            "upstreamConnections": ["fs-churn", "is-churn"],
+            "downstreamConnections": ["ds-hogan"]
+          }
+        ],
+        "featureStores": [
+          {
+            "id": "fs-churn",
+            "name": "Churn feature Store",
+            "type": "FEATURE_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8,
+              "workflows": 1
+            },
+            "upstreamConnections": ["model-churn", "model-churn-mitigation"],
+            "downstreamConnections": [
+              "entity-customer",
+              "entity-invoices",
+              "entity-transactions",
+              "entity-products"
+            ]
+          },
+          {
+            "id": "fs-product-recommendation",
+            "name": "Product Recommendation Feature Store",
+            "type": "FEATURE_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 10,
+              "workflows": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ],
+        "insightStores": [
+          {
+            "id": "is-churn",
+            "name": "Churn Insights Store",
+            "type": "INSIGHTS_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8,
+              "workflows": 1
+            },
+            "upstreamConnections": ["model-churn", "model-churn-mitigation"],
+            "downstreamConnections": [
+              "entity-customer",
+              "entity-invoices",
+              "entity-transactions",
+              "entity-products"
+            ]
+          },
+          {
+            "id": "insight-churn-data",
+            "name": "Churn Insights Data",
+            "type": "INSIGHTS_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 6,
+              "workflows": 1
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          },
+          {
+            "id": "insight-product-recommendation",
+            "name": "Product Recommendation Insights data",
+            "type": "INSIGHTS_STORE",
+            "version": "V 1.2",
+            "metadata": {
+              "fields": 8,
+              "workflows": 2
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ],
+        "dataSources": [
+          {
+            "id": "ds-hogan",
+            "name": "Hogan Banking Core",
+            "type": "DATA_SOURCE",
+            "version": "V 1.2",
+            "metadata": {
+              "files": 12,
+              "fields": 45
+            },
+            "upstreamConnections": [
+              "entity-customer",
+              "entity-invoices",
+              "entity-transactions",
+              "entity-products"
+            ],
+            "downstreamConnections": []
+          },
+          {
+            "id": "ds-salesforce",
+            "name": "Salesforce CRM",
+            "type": "DATA_SOURCE",
+            "version": "V 1.2",
+            "metadata": {
+              "files": 8,
+              "fields": 32
+            },
+            "upstreamConnections": [],
+            "downstreamConnections": []
+          }
+        ]
+      }
+    },
+    {
+      "name": "LYZA",
+      "description": "Multi-Agent System (MAS) designed to empower users to create AI application",
+      "system_prompt": "# 🧠 System Prompt: Multi-Agent System for Profitability Optimization\n\n## 🎯 System Objective\n**Leverage a self-directed Multi-Agent System (MAS) to enhance the profitability of the target product by 6%.**\n\n## 🧑‍💼 Primary User Persona\n- **Role**: Product Manager  \n- **Goals**:\n  - Deliver proactive insights on market trends and customer needs.\n  - Enable data-driven decision-making for revenue and strategic development.\n  - Identify opportunities through pricing, feature prioritization, and resource allocation.\n  - Align product direction with user behavior to boost loyalty and retention.\n\n\n## 🧠 System Architecture & Agents\n\n### 1. Market Trends Agent\n- Scrapes and synthesizes industry news, competitor moves, and consumer behavior.\n- Forecasts market demand shifts.\n- **Outputs**: Trend dashboards, early warnings, opportunity maps.\n\n### 2. Customer Intelligence Agent\n- Analyzes interaction logs, reviews, NPS, and churn indicators.\n- Segments users by behavior, sentiment, and value.\n- **Outputs**: Loyalty drivers, friction points, feature adoption trends.\n\n### 3. Pricing & Profitability Agent\n- Simulates pricing and bundling strategies using internal and competitive data.\n- Optimizes for revenue per user, margin, and LTV/CAC.\n- **Outputs**: Dynamic pricing recs, test strategies.\n\n### 4. Feature Prioritization Agent\n- Evaluates feature ROI using A/B test data, analytics, and requests.\n- Prioritizes by impact, feasibility, alignment.\n- **Outputs**: Roadmap priorities with ROI scoring.\n\n### 5. Strategic Alignment Agent\n- Maps recommendations to business OKRs and product KPIs.\n- Aligns output with executive vision.\n- **Outputs**: OKR scorecards, strategic impact alerts.\n\n---\n\n## 📊 Key Performance Indicators (KPIs)\n\n| KPI | Target | Measured By |\n|-----|--------|-------------|\n| **Product Profitability Uplift** | +6% | (Revenue - COGS)/Revenue |\n| **Customer Lifetime Value (LTV)** | +10% | Avg. revenue per customer lifecycle |\n| **Churn Rate** | -15% | % of users leaving per month |\n| **Feature Adoption Rate** | +20% | % of users using new features |\n| **ARPU (Avg. Revenue/User)** | +5% | Revenue ÷ Active Users |\n| **Time-to-Insight** | -30% | Data → Action latency |\n| **Insight Utilization Rate** | +40% | % of insights influencing actions |\n\n---\n\n## 🔍 Sample Insights\n\n### Market-Driven\n- \"Gen Z shift to mobile-first productivity tools = 12% drop in desktop use.\"\n- \"Competitor pricing shift caused 8% churn in overlapping user base.\"\n\n### Customer Behavior\n- \"Low onboarding completion = 3x higher churn.\"\n- \"Power users love Feature X; UI promotion could lift adoption by 15%.\"\n\n### Profitability Levers\n- \"Feature A + B bundle → +9% profit in Tier 2 users.\"\n- \"Proactive support bot reduces per-user cost → +2% margin.\"\n\n### Feature ROI\n- \"Feature C = $480K/year projected uplift.\"\n- \"Feature B = high dev cost, <1% revenue impact — deprioritize.\"\n\n### Strategic Forecasts\n- \"Entering Vertical Y in 6 months → +15% LTV based on market signals.\"\n\n---\n\n## 🧩 Data Assets Utilized\n\n- **Product Analytics**: Mixpanel, Amplitude, GA\n- **CRM & Sales**: Salesforce, HubSpot\n- **Customer Feedback**: NPS, Zendesk, UserVoice\n- **Behavioral Tools**: Segment, FullStory, Heap\n- **Financial Systems**: ERP, P&L Data\n- **Competitive Data**: SimilarWeb, AppAnnie\n- **Custom Data**: Proprietary usage and support metrics\n\n---\n\n## 🔄 Decision Loop & Agent Autonomy\n\n- **Central Coordination Hub** integrates agent output.\n- Resolves conflicts, ranks ideas by profitability impact.\n- Proposes action plans with data traceability.\n- **Escalation** to Product Manager for high-impact decisions.\n\n---\n\n## 🔐 Governance, Control & Guardrails\n\n- **Human-in-the-loop** for major product/pricing decisions.\n- **Bias detection** on predictive models.\n- **Explainability** for all recommendations (with data trace).\n- **Audit logs** for decision transparency.\n\n---\n\n## 📅 Weekly Outputs\n\n- **Executive Summary**: Top 5 profitability drivers.\n- **Feature ROI Tracker**: Updated roadmap impacts.\n- **Customer Health Report**: Segments at risk/opportunity.\n- **Pricing Simulations**: Scenarios with projected profit impact.\n- **Agent Confidence Scores**: Trust levels per suggestion.\n\n---\n\n## ✅ Summary\n\nA self-directed MAS empowers the Product Manager to:\n- Predict market trends.\n- Act on user needs.\n- Make smarter roadmap and pricing decisions.\n- Achieve a sustained 6%+ profitability uplift with explainable, data-backed insights.",
+      "mas": [
+        {
+          "name": "Enrich360 Offline Process",
+          "description": "Batch enrichment engine designed for large-scale data processing, ensuring accuracy and consistency at scale",
+          "updated_at": "2025-06-04T05:54:09+00:00",
+          "tags": ["assistants", "agents", "MAS"],
+          "id": "532ed470-b97d-4171-8121-07fbff800728",
+          "folder_id": "a2956334-e842-44ac-96aa-7190bfa5396c"
+        },
+        {
+          "name": "Enrich360 Interactive",
+          "description": "Empowers product managers with real-time, user-driven insights to make faster, data-backed decisions",
+          "updated_at": "2025-06-04T05:54:20+00:00",
+          "tags": ["assistants", "agents", "MAS"],
+          "id": "f8d4f2f9-5285-45b0-8eda-cd0043e230e3",
+          "folder_id": "a2956334-e842-44ac-96aa-7190bfa5396c"
+        }
+      ]
+    },
+    {
+      "name": "Presentations",
+      "description": "Visual insights and demos showcasing Experience 360 capabilities.",
+      "deployed_urls": [
+        {
+          "url": "/intarc/dashboard",
+          "description": "This is where the Enrich360 UI is deployed. Click to open the live instance."
+        }
+      ]
+    },
+    {
+      "name": "Deployment",
+      "description": "Tools and settings to launch, monitor, and manage AI solution in real-time environments.",
+      "configuration": "Kubernetes",
+      "version": "V 1.2",
+      "replicas": {
+        "model": 3,
+        "agent": 2,
+        "logging": 1,
+        "monitoring": 1
+      },
+      "yaml": "# -----------------------------------------------------\n# enrich360 AI Model Deployment\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-model\n  labels:\n    app: enrich360\n    component: model\nspec:\n  replicas: 3\n  selector:\n    matchLabels:\n      app: enrich360\n      component: model\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: model\n    spec:\n      containers:\n      - name: model-server\n        image: enrich360/model-server:latest\n        ports:\n        - containerPort: 8000\n        env:\n        - name: MODEL_PATH\n          value: /models/classifier-v2.pth\n        - name: LOG_LEVEL\n          value: info\n        volumeMounts:\n        - name: model-storage\n          mountPath: /models\n      volumes:\n      - name: model-storage\n        persistentVolumeClaim:\n          claimName: enrich360-model-pvc\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-model-service\nspec:\n  selector:\n    app: enrich360\n    component: model\n  ports:\n  - port: 80\n    targetPort: 8000\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# enrich360 Agent (AI Decision-Maker)\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-agent\n  labels:\n    app: enrich360\n    component: agent\nspec:\n  replicas: 2\n  selector:\n    matchLabels:\n      app: enrich360\n      component: agent\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: agent\n    spec:\n      containers:\n      - name: agent-service\n        image: enrich360/agent:stable\n        ports:\n        - containerPort: 8500\n        env:\n        - name: MODEL_API_URL\n          value: http://enrich360-model-service/predict\n        - name: AGENT_MODE\n          value: production\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-agent-service\nspec:\n  selector:\n    app: enrich360\n    component: agent\n  ports:\n  - port: 85\n    targetPort: 8500\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# enrich360 Logging Service (e.g., Fluentd, Loki)\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-logging\n  labels:\n    app: enrich360\n    component: logging\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: enrich360\n      component: logging\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: logging\n    spec:\n      containers:\n      - name: logger\n        image: enrich360/logging:latest\n        ports:\n        - containerPort: 24224\n        volumeMounts:\n        - name: log-storage\n          mountPath: /var/log/enrich360\n      volumes:\n      - name: log-storage\n        emptyDir: {}\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-logging-service\nspec:\n  selector:\n    app: enrich360\n    component: logging\n  ports:\n  - port: 24224\n    targetPort: 24224\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# enrich360 Monitoring Dashboard (e.g., Prometheus + Grafana)\n# -----------------------------------------------------\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: enrich360-monitoring\n  labels:\n    app: enrich360\n    component: monitoring\nspec:\n  replicas: 1\n  selector:\n    matchLabels:\n      app: enrich360\n      component: monitoring\n  template:\n    metadata:\n      labels:\n        app: enrich360\n        component: monitoring\n    spec:\n      containers:\n      - name: prometheus\n        image: prom/prometheus:latest\n        ports:\n        - containerPort: 9090\n        volumeMounts:\n        - name: prom-config\n          mountPath: /etc/prometheus\n      volumes:\n      - name: prom-config\n        configMap:\n          name: enrich360-prometheus-config\n\n---\napiVersion: v1\nkind: Service\nmetadata:\n  name: enrich360-monitoring-service\nspec:\n  selector:\n    app: enrich360\n    component: monitoring\n  ports:\n  - port: 90\n    targetPort: 9090\n  type: ClusterIP\n\n---\n# -----------------------------------------------------\n# Persistent Volume Claim for Model Storage\n# -----------------------------------------------------\napiVersion: v1\nkind: PersistentVolumeClaim\nmetadata:\n  name: enrich360-model-pvc\nspec:\n  accessModes:\n    - ReadWriteOnce\n  resources:\n    requests:\n      storage: 2Gi\n\n---\n# -----------------------------------------------------\n# ConfigMap for Prometheus Configuration (Example)\n# -----------------------------------------------------\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: enrich360-prometheus-config\ndata:\n  prometheus.yml: |\n    global:\n      scrape_interval: 15s\n    scrape_configs:\n      - job_name: 'enrich360'\n        static_configs:\n          - targets: ['enrich360-model-service:80', 'enrich360-agent-service:85']",
+      "services": [
+        "enrich360-model-service",
+        "enrich360-agent-service",
+        "enrich360-logging-service",
+        "enrich360-monitoring-service"
+      ],
+      "endpoints": [
+        {
+          "name": "Get Revenue Optimizer",
+          "description": "AI Agent",
+          "url": "/ai-agent",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Alerts",
+          "description": "Dataset",
+          "url": "/dataset",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Product Metrics",
+          "description": "Dashboard",
+          "url": "/dashboard",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Churn Management Insights",
+          "description": "ML Model",
+          "url": "/ml-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Prospect Identification Insights",
+          "description": "Model",
+          "url": "/model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Market Insights",
+          "description": "Gen AI Model",
+          "url": "/gen-ai-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Customer Sentiment",
+          "description": "ML Model",
+          "url": "/ml-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Competitor Watch",
+          "description": "Gen AI Model",
+          "url": "/gen-ai-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Get Suggested Questions",
+          "description": "Gen AI Model",
+          "url": "/gen-ai-model",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "LYZA Enrich360 MAS",
+          "description": "Enrich360 MAS",
+          "url": "/enrich360-mas",
+          "version": "1.0.0",
+          "status": "Active"
+        },
+        {
+          "name": "Authentication Service",
+          "description": "Handles user authentication and authorization",
+          "url": "/auth",
+          "version": "1.0.0",
+          "status": "Active"
+        }
+      ]
+    },
+    {
+      "name": "KPI",
+      "description": "Dashboard tracking key performance indicators to evaluate AI application effectiveness.",
+      "business": [
+        {
+          "name": "Revenue",
+          "description": "Overall Revenue Targets",
+          "id": "kpi-business-001",
+          "url": "/kpis/revenue",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-4%",
+          "target": "$100.3M"
+        },
+        {
+          "name": "Profitability",
+          "description": "Product Profitability",
+          "id": "kpi-business-002",
+          "url": "/kpis/profitability",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-6%",
+          "target": "45%"
+        },
+        {
+          "name": "Cost to Serve",
+          "description": "Cost to Serve my product",
+          "id": "kpi-business-003",
+          "url": "/kpis/cost-to-serve",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-2.5%",
+          "target": "$18.2M"
+        },
+        {
+          "name": "Churn Rate",
+          "description": "Target churn rate of customers",
+          "id": "kpi-business-004",
+          "url": "/kpis/churn-rate",
+          "version": "V 1.2",
+          "status": "Improving",
+          "trend": "+2%",
+          "target": "12.5%"
+        },
+        {
+          "name": "Product Usage",
+          "description": "Transactions",
+          "id": "kpi-business-005",
+          "url": "/kpis/product-usage",
+          "version": "V 1.2",
+          "status": "Declining",
+          "trend": "-$2.35M",
+          "target": "24.5M"
+        },
+        {
+          "name": "Waivers",
+          "description": "Product Waivers",
+          "id": "kpi-business-006",
+          "url": "/kpis/waivers",
+          "version": "V 1.2",
+          "status": "Improving",
+          "trend": "+11.3%",
+          "target": "$9.6M"
+        }
+      ],
+      "technical": [
+        {
+          "name": "Processing Efficiency",
+          "description": "Current processing efficiency rate",
+          "id": "kpi-technical-001",
+          "url": "/kpis/processing-efficiency",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "98%",
+          "target": "95%",
+          "trend": "+3% from last month"
+        },
+        {
+          "name": "Error Rate",
+          "description": "System error occurrence rate",
+          "id": "kpi-technical-002",
+          "url": "/kpis/error-rate",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "1.2%",
+          "target": "<2%",
+          "trend": "-0.5% from last month"
+        },
+        {
+          "name": "Response Time",
+          "description": "Average API response time",
+          "id": "kpi-technical-003",
+          "url": "/kpis/response-time",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "150ms",
+          "target": "<200ms",
+          "trend": "-50ms from last month"
+        },
+        {
+          "name": "Uptime",
+          "description": "System availability percentage",
+          "id": "kpi-technical-004",
+          "url": "/kpis/uptime",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "99.9%",
+          "target": "99.9%",
+          "trend": "+0.1% from last month"
+        },
+        {
+          "name": "Data Accuracy",
+          "description": "Data validation success rate",
+          "id": "kpi-technical-005",
+          "url": "/kpis/data-accuracy",
+          "version": "V 1.2",
+          "status": "Active",
+          "current": "99.5%",
+          "target": "99%",
+          "trend": "+0.5% from last month"
+        }
+      ]
+    },
+    {
+      "name": "Reports",
+      "description": "Generated summaries and logs detailing system performance and agent behavior.",
+      "reports": [
+        {
+          "name": "Performance Report",
+          "description": "Detailed analysis of system performance metrics",
+          "id": "report-performance-001",
+          "url": "/reports/performance",
+          "version": "V 1.2",
+          "status": "Active",
+          "last_updated": "Today"
+        },
+        {
+          "name": "Usage Analytics",
+          "description": "User engagement and system utilization statistics",
+          "id": "report-usage-analytics-001",
+          "url": "/reports/usage-analytics",
+          "version": "V 1.2",
+          "status": "Active",
+          "last_updated": "Today"
+        },
+        {
+          "name": "Error Log Report",
+          "description": "Comprehensive error tracking and resolution status",
+          "id": "report-error-log-001",
+          "url": "/reports/error-logs",
+          "version": "V 1.2",
+          "status": "Active",
+          "last_updated": "Today"
+        }
+      ]
+    }
+  ]
+}
diff --git a/intelliarcs/__intelliarcs/meta.json b/intelliarcs/__intelliarcs/meta.json
new file mode 100644
index 0000000..5d32846
--- /dev/null
+++ b/intelliarcs/__intelliarcs/meta.json
@@ -0,0 +1,26 @@
+[
+  {
+    "id": "experience-360",
+    "file": "experience-360.json",
+    "name": "Experience 360",
+    "description": "Revolutionize customer engagement with Experience360 a powerful AI-driven platform designed for both agents and customers.",
+    "status": "87% Complete",
+    "statusType": "progress"
+  },
+  {
+    "id": "exceptions-360",
+    "file": "exceptions-360.json",
+    "name": "Exceptions 360",
+    "description": "Smart, all-in-one platform for managing exceptions with ease. By integrating seamlessly with systems like CCS and C2M, it empowers teams to track, resolve, and streamline exception handling—all from one centralized hub.",
+    "status": "Not Set Up",
+    "statusType": "inactive"
+  },
+  {
+    "id": "enrich-360",
+    "file": "enrich-360.json",
+    "name": "Enrich 360",
+    "description": "Empower product managers with proactive, actionable insights that drive revenue growth, boost profitability, and build lasting customer loyalty.",
+    "status": "Running",
+    "statusType": "active"
+  }
+]