{ "id": "Enrich360", "name": "Enrich360", "description": "Optimize qualification effectiveness for tiered customer programs using AI-driven insights to boost engagement and profitability.", "status": "87% Complete", "statusType": "progress", "tabs": [ { "name": "Overview", "description": "Optimize qualification effectiveness for tiered customer programs using AI-driven insights to boost engagement and profitability.", "goals": [ "Increase overall qualification effectiveness by 10%", "Enhance customer engagement metrics by optimizing tier criteria" ], "objective": "Leverage a self-directed Multi-Agent System to achieve improvements in qualification rates and customer activity.", "roles": [ { "name": "Product Manager", "description": "" } ], "benefits": [ "Provide proactive recommendations on tier adjustments to anticipate customer behaviors", "Support data-driven decisions for better resource allocation and feature bundling", "Identify opportunities to reduce passive qualifications and increase active engagements", "Improve customer retention by aligning tiers with usage patterns and feedback" ] }, { "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-offers-and-rewards", "agent-balance-prediction", "agent-product-optimization", "agent-competitor-insights", "agent-tier-movement", "agent-qualification-effectiveness", "agent-customer-segmentation", "agent-churn-management" ] } ], "agents": [ { "id": "agent-offers-and-rewards", "name": "Offers and Rewards Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Designs personalized incentives to boost engagement and retention" }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "2773", "model-churn-mitigation" ] }, { "id": "agent-churn-management", "name": "Churn Management Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Predicts and mitigates customer attrition using behavioral patterns" }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "2773", "model-churn-mitigation" ] }, { "id": "agent-balance-prediction", "name": "Balance Forecasting Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Forecasts account balances using historical and transactional data trends." }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "model-balance-prediction" ] }, { "id": "agent-product-optimization", "name": "Product Optimization Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Identifies ideal pricing strategies for products to maximize revenue and satisfaction" }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "model-product-optimization" ] }, { "id": "agent-competitor-insights", "name": "Competitor Insights Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Analyzes competitor trends to uncover market opportunities and threats." }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "tool-kb", "tool-epm-mcp" ] }, { "id": "agent-tier-movement", "name": "Tier Movement Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Tracks and predicts customer movement across loyalty or account tiers." }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "model-tier-movement" ] }, { "id": "agent-qualification-effectiveness", "name": "Qualification Effectiveness Agent", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Evaluates effectiveness of customer qualification criteria." }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "model-balance-prediction", "model-product-optimization", "model-usage-classification", "model-tier-movement", "model-usage-forecasting", "model-customer-segmentation", "model-refund-forecasting", "tool-lakehouse", "tool-kb", "tool-chart-generation", "tool-web-search", "tool-epm-mcp" ] }, { "id": "agent-customer-segmentation", "name": "Customer Segmentation", "type": "AGENT", "version": "V 1.2", "metadata": { "description": "Clusters customers by behavior, value, and engagement for targeting." }, "upstreamConnections": [ "orchestrator-1" ], "downstreamConnections": [ "model-similar-accounts", "model-usage-classification" ] } ], "models": [ { "id": "2773", "name": "Likelihood of Churn Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 8, "size": "1 GB" }, "upstreamConnections": [ "agent-offers-and-rewards" ], "downstreamConnections": [ "fs-churn", "is-churn" ] }, { "id": "model-churn-mitigation", "name": "Churn Mitigation Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 10, "size": "1.5 GB" }, "upstreamConnections": [ "agent-offers-and-rewards" ], "downstreamConnections": [ "fs-churn", "is-churn" ] }, { "id": "model-balance-prediction", "name": "Balance Prediction Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 12, "size": "1 GB" }, "upstreamConnections": [ "agent-balance-prediction", "agent-qualification-effectiveness" ], "downstreamConnections": [ "fs-balance-history" ] }, { "id": "model-refund-forecasting", "name": "Refund Forecasting Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 12, "size": "2 GB" }, "upstreamConnections": [ "agent-product-optimization" ], "downstreamConnections": [ "fs-product", "fs-balance-history", "fs-event-history", "fs-monthly-deposit" ] }, { "id": "model-product-optimization", "name": "Product Optimization Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 8, "size": "1 GB" }, "upstreamConnections": [ "agent-product-optimization", "agent-qualification-effectiveness" ], "downstreamConnections": [ "fs-product", "fs-account", "fs-customer-segmentation", "fs-event-history", "fs-eligible-offers" ] }, { "id": "model-tier-movement", "name": "Tier Movement Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 10, "size": "1 GB" }, "upstreamConnections": [ "agent-tier-movement", "agent-qualification-effectiveness" ], "downstreamConnections": [ "fs-product", "fs-balance-history", "fs-customer-segmentation", "fs-account", "fs-event-history", "is-tier" ] }, { "id": "model-customer-segmentation", "name": "Customer Segmentation Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 10, "size": "1 GB" }, "upstreamConnections": [ "agent-qualification-effectiveness" ], "downstreamConnections": [ "fs-customer-segmentation", "fs-account", "fs-product", "fs-balance-history", "is-engagement" ] }, { "id": "model-usage-classification", "name": "Usage Classification Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 8, "size": "1 GB" }, "upstreamConnections": [ "agent-customer-segmentation", "agent-qualification-effectiveness" ], "downstreamConnections": [ "fs-monthly-deposit" ] }, { "id": "model-usage-forecasting", "name": "Usage Forecasting Model", "type": "MODEL", "version": "V 1.2", "metadata": { "parameters": 8, "size": "1 GB" }, "upstreamConnections": [ "agent-qualification-effectiveness" ], "downstreamConnections": [ "fs-monthly-deposit", "fs-event-history" ] } ], "tools": [ { "id": "tool-batch", "name": "Batch job", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 4 }, "upstreamConnections": [ "2773" ], "downstreamConnections": [ "fs-churn" ] }, { "id": "tool-chart-generation", "name": "Chart Generation Tool", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 4 }, "upstreamConnections": [ "agent-tier-movement", "model-qualification-effectiveness", "agent-qualification-effectiveness" ], "downstreamConnections": [] }, { "id": "tool-epm-mcp", "name": "EPM MCP tool", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 2 }, "upstreamConnections": [ "agent-qualification-effectiveness", "agent-competitor-insights" ], "downstreamConnections": [] }, { "id": "tool-model-inference", "name": "Model inference tool", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 3 }, "upstreamConnections": [ "model-qualification-effectiveness", "agent-qualification-effectiveness" ], "downstreamConnections": [] }, { "id": "tool-web-search", "name": "Web Search Tool", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 2 }, "upstreamConnections": [ "agent-competitor-insights", "agent-qualification-effectiveness" ], "downstreamConnections": [] }, { "id": "tool-kb", "name": "Knowledge Base Tool", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 2 }, "upstreamConnections": [ "agent-competitor-insights", "agent-qualification-effectiveness" ], "downstreamConnections": [ "kb-first-citizen-web-data", "kb-capitalone-web-data", "kb-chase-web-data", "kb-td-web-data" ] }, { "id": "tool-lakehouse", "name": "Lakehouse Connector Tool", "type": "TOOL", "version": "V 1.2", "metadata": { "interfaces": 2 }, "upstreamConnections": [ "agent-qualification-effectiveness", "model-qualification-effectiveness" ], "downstreamConnections": [] } ], "dataEntities": [ { "id": "entity-customer", "name": "Customer", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 15 }, "upstreamConnections": [ "fs-churn", "is-churn", "fs-monthly-deposit", "is-qualification", "fs-tier-history", "fs-eligible-offers", "fs-account", "fs-customer-segmentation" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "entity-account", "name": "Account", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 12 }, "upstreamConnections": [ "fs-churn", "is-churn", "fs-tier-history", "fs-balance-history", "fs-account", "fs-customer-segmentation" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "entity-transactions", "name": "Transactions", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 18 }, "upstreamConnections": [ "fs-churn", "is-churn", "fs-monthly-deposit", "fs-customer-segmentation", "fs-event-history" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "entity-balances", "name": "Balances", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 21 }, "upstreamConnections": [ "fs-tier-history", "fs-event-history", "fs-balance-history", "fs-monthly-deposit" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "entity-products", "name": "Products", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 8 }, "upstreamConnections": [ "fs-churn", "is-churn", "fs-eligible-offers", "fs-tier-history", "fs-product", "fs-customer-segmentation", "fs-event-history" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "entity-charge", "name": "Charges", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 8 }, "upstreamConnections": [ "fs-churn", "is-churn", "fs-eligible-offers", "fs-tier-history", "fs-monthly-deposit", "fs-customer-segmentation", "fs-event-history" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "POSTGRES/EPM_CA/folder/pricelist", "name": "Pricing", "type": "DATA_ENTITY", "version": "V 1.2", "metadata": { "fields": 8 }, "upstreamConnections": [ "fs-eligible-offers", "fs-tier-history", "fs-monthly-deposit", "fs-product" ], "downstreamConnections": [ "POSTGRES/EPM_CA" ] }, { "id": "kb-first-citizen-web-data", "name": "First Citizens Web Data", "type": "KNOWLEDGE_BASE", "version": "V 1.2", "metadata": { "web_urls": 1382 }, "upstreamConnections": [ "tool-kb" ], "downstreamConnections": [] }, { "id": "kb-chase-web-data", "name": "Chase Web Data", "type": "KNOWLEDGE_BASE", "version": "V 1.2", "metadata": { "web_urls": 362 }, "upstreamConnections": [ "tool-kb" ], "downstreamConnections": [] }, { "id": "kb-td-web-data", "name": "TD Web Data", "type": "KNOWLEDGE_BASE", "version": "V 1.2", "metadata": { "web_urls": 4366 }, "upstreamConnections": [ "tool-kb" ], "downstreamConnections": [] }, { "id": "kb-capitalone-web-data", "name": "Capitalone Web Data", "type": "KNOWLEDGE_BASE", "version": "V 1.2", "metadata": { "web_urls": 3627 }, "upstreamConnections": [ "tool-kb" ], "downstreamConnections": [] } ], "featureStores": [ { "id": "fs-churn", "name": "Churn feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "2773", "model-churn-mitigation" ], "downstreamConnections": [ "entity-customer", "entity-account", "entity-transactions", "entity-charge", "entity-products" ] }, { "id": "fs-product", "name": "Product feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-product-optimization", "model-tier-movement", "model-refund-forecasting", "model-customer-segmentation" ], "downstreamConnections": [ "entity-products", "POSTGRES/EPM_CA/folder/pricelist" ] }, { "id": "fs-eligible-offers", "name": "Eligible offers Feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 10, "workflows": 2, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}, {"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-qualification-effectiveness", "model-product-optimization" ], "downstreamConnections": [ "entity-products", "entity-customer", "POSTGRES/EPM_CA/folder/pricelist" ] }, { "id": "fs-monthly-deposit", "name": "Monthly enagement Feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 10, "workflows": 2, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}, {"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-balance-prediction", "model-refund-forecasting" ], "downstreamConnections": [ "entity-customer", "entity-transactions", "entity-balances", "entity-charge", "POSTGRES/EPM_CA/folder/pricelist" ] }, { "id": "fs-event-history", "name": "Transaction Events Feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}, {"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-qualification-effectiveness", "model-product-optimization", "model-balance-prediction", "model-refund-forecasting", "model-tier-movement" ], "downstreamConnections": [ "entity-products", "entity-charge", "entity-transactions", "entity-balances" ] }, { "id": "fs-balance-history", "name": "Balance History Feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-balance-prediction", "model-tier-movement", "model-customer-segmentation" ], "downstreamConnections": [ "entity-balances", "entity-account" ] }, { "id": "fs-customer-segmentation", "name": "Customer Segmentation", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-customer-segmentation", "model-tier-movement", "model-product-optimization" ], "downstreamConnections": [ "entity-charge", "entity-products", "entity-transactions", "entity-customer", "entity-account" ] }, { "id": "fs-account", "name": "Account Feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-customer-segmentation", "model-tier-movement", "model-product-optimization" ], "downstreamConnections": [ "entity-customer", "entity-account" ] }, { "id": "fs-tier-history", "name": "Tier historical Feature Store", "type": "FEATURE_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-customer-segmentation", "model-tier-movement" ], "downstreamConnections": [ "entity-charge", "entity-products", "POSTGRES/EPM_CA/folder/pricelist", "entity-customer", "entity-account", "entity-balances" ] } ], "insightStores": [ { "id": "is-churn", "name": "Churn Insights Store", "type": "INSIGHTS_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "2773", "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, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [], "downstreamConnections": [] }, { "id": "insight-product-recommendation", "name": "Product Recommendation Insights data", "type": "INSIGHTS_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 2, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}, {"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [], "downstreamConnections": [] }, { "id": "is-qualification", "name": "Qualification Insights Store", "type": "INSIGHTS_STORE", "version": "V 1.2", "metadata": { "fields": 9, "workflows": 2, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}, {"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-qualification-effectiveness" ], "downstreamConnections": [ "entity-customer", "entity-eligible-transactions-events", "entity-recommendation" ] }, { "id": "is-engagement", "name": "Engagement Insights Store", "type": "INSIGHTS_STORE", "version": "V 1.2", "metadata": { "fields": 7, "workflows": 1, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-time-series" ], "downstreamConnections": [ "entity-tier" ] }, { "id": "is-tier", "name": "Tier Insights store", "type": "INSIGHTS_STORE", "version": "V 1.2", "metadata": { "fields": 8, "workflows": 2, "workflows_data": [{"name": "Balance_Prediction_EPM_CAA_Feature_Store"}, {"name": "Balance_Prediction_EPM_CAA_Feature_Store"}] }, "upstreamConnections": [ "model-tier-movement" ], "downstreamConnections": [] } ], "dataSources": [ { "id": "ds-systematics", "name": "Systematics Banking Core", "type": "DATA_SOURCE", "version": "V 1.2", "metadata": { "files": 12, "fields": 45 }, "upstreamConnections": [], "downstreamConnections": [] }, { "id": "POSTGRES/EPM_CA", "name": "Enterprise Profit Maximization", "type": "DATA_SOURCE", "version": "V 1.2", "metadata": { "files": 8, "fields": 32 }, "upstreamConnections": [ "entity-customer", "entity-account", "entity-transactions", "entity-balances", "entity-products", "entity-charge", "POSTGRES/EPM_CA/folder/pricelist" ], "downstreamConnections": [] } ] } }, { "name": "LYZA", "description": "Multi-Agent System (MAS) designed to empower users to create AI application", "system_prompt": "# 🧠 System Prompt: Multi-Agent System for Qualification Optimization\n\n## 🎯 System Objective\n**Leverage a self-directed Multi-Agent System (MAS) to enhance qualification effectiveness and engagement by 10%.**\n\n## 🧑‍💼 Primary User Persona\n- **Role**: Product Manager \n- **Goals**:\n - Provide insights on tier criteria and customer behaviors.\n - Enable decisions for threshold adjustments and bundling.\n - Optimize for active engagement and reduce passive qualifications.\n - Align tiers with usage to improve retention.\n\n\n## 🧠 System Architecture & Agents\n\n### 1. Data Ingestion Agent\n- Fetches and processes data from sources.\n- **Outputs**: Cleaned datasets.\n\n### 2. Analysis Agent\n- Identifies patterns and concentrations.\n- **Outputs**: Descriptive insights.\n\n### 3. Prediction Agent\n- Forecasts impacts of changes.\n- **Outputs**: Predictive simulations.\n\n### 4. Optimization Agent\n- Suggests optimal adjustments.\n- **Outputs**: Optimized criteria.\n\n### 5. Recommendation Agent\n- Generates actionable suggestions.\n- **Outputs**: Strategic recommendations.\n\n### 6. Validation Agent\n- Validates outputs.\n- **Outputs**: Refined insights.\n\n---\n\n## 📊 Key Performance Indicators (KPIs)\n\n| KPI | Target | Measured By |\n|-----|--------|-------------|\n| **Qualification Effectiveness Uplift** | +10% | Qualification rate |\n| **Engagement Rate** | +15% | Active users/events |\n| **Passive Reduction** | -20% | Passive qualifiers |\n| **Tier Movement Rate** | +12% | Up-tier migrations |\n| **Customer Retention** | +8% | Retention rate |\n\n---\n\n## 🔍 Sample Insights\n\n### Engagement-Driven\n- \"Increasing direct deposit threshold could boost active users by 5%.\"\n\n### Optimization Levers\n- \"Bundle bill pay with auto transfer for 12% engagement lift.\"\n\n---\n\n## 🧩 Data Assets Utilized\n\n- **Customer Data**: Profiles, tenures.\n- **Transactional Data**: Events, usages.\n- **Engagement Metrics**: Active rates.\n\n---\n\n## 🔄 Decision Loop & Agent Autonomy\n\n- **Central Hub** integrates outputs.\n- Proposes plans with traceability.\n\n---\n\n## 🔐 Governance\n\n- **Human-in-the-loop** for decisions.\n- **Explainability** for recs.\n\n---\n\n## 📅 Weekly Outputs\n\n- **Summary**: Top optimizations.\n- **Impact Tracker**: Projected lifts.\n\n---\n\n## ✅ Summary\n\nEmpowers managers to optimize qualifications with 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 Enrich360 capabilities for qualification optimization.", "deployed_urls": [ { "url": "https://td.demo2.epbcloud.org/FPB/dashboard/command-center/qualification-effectiveness", "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 solutions 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 for Qualification Optimization\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 Qualification Optimizer", "description": "AI Agent", "url": "/ai-agent", "version": "1.0.0", "status": "Active" }, { "name": "Get Tier Insights", "description": "Dataset", "url": "/dataset", "version": "1.0.0", "status": "Active" }, { "name": "Get Engagement Metrics", "description": "Dashboard", "url": "/dashboard", "version": "1.0.0", "status": "Active" }, { "name": "Get Qualification Management Insights", "description": "ML Model", "url": "/ml-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 Churning", "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": "Engagement", "description": "Overall Engagement Targets", "id": "kpi-business-001", "url": "/kpis/engagement", "version": "V 1.2", "status": "Improving", "trend": "+5%", "target": "50%" }, { "name": "Qualification Rate", "description": "Qualification Effectiveness", "id": "kpi-business-002", "url": "/kpis/qualification", "version": "V 1.2", "status": "Improving", "trend": "+8%", "target": "60%" }, { "name": "Active Users", "description": "Active User Growth", "id": "kpi-business-003", "url": "/kpis/active-users", "version": "V 1.2", "status": "Stable", "trend": "+3%", "target": "75%" }, { "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": "Effectiveness Report", "description": "Detailed analysis of qualification effectiveness metrics", "id": "report-effectiveness-001", "url": "/reports/effectiveness", "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" } ] } ] }