diff --git a/__intelliarcs/exceptions-360.json b/__intelliarcs/exceptions-360.json deleted file mode 100644 index 01fbd74..0000000 --- a/__intelliarcs/exceptions-360.json +++ /dev/null @@ -1,830 +0,0 @@ -{ - "id": "experience-360", - "name": "Exceptions 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", - "340e80ac-f9ce-402f-a9c6-06370cf3f070" - ] - } - ], - "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": "340e80ac-f9ce-402f-a9c6-06370cf3f070", - "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": "232", - "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": "# ๐Ÿง  System Prompt: Multi-Agent System for Profitability Optimization\n\n## ๐ŸŽฏ System Objective\n**Leverage a self-directed Multi-Agent System (MAS) to enhance the profitability of the target product by 6%.**\n\n## ๐Ÿง‘โ€๐Ÿ’ผ 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## ๐Ÿง  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## ๐Ÿ“Š 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 รท Active Users |\n| **Time-to-Insight** | -30% | Data โ†’ Action latency |\n| **Insight Utilization Rate** | +40% | % of insights influencing actions |\n\n---\n\n## ๐Ÿ” 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 โ†’ +9% profit in Tier 2 users.\"\n- \"Proactive support bot reduces per-user cost โ†’ +2% margin.\"\n\n### Feature ROI\n- \"Feature C = $480K/year projected uplift.\"\n- \"Feature B = high dev cost, <1% revenue impact โ€” deprioritize.\"\n\n### Strategic Forecasts\n- \"Entering Vertical Y in 6 months โ†’ +15% LTV based on market signals.\"\n\n---\n\n## ๐Ÿงฉ 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## ๐Ÿ”„ 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## ๐Ÿ” 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## ๐Ÿ“… 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## โœ… 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" - } - ] - } - ] -}