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Enterprise AI Assistant Platform

Created by: Pramod Thebe


Generative AI often fails inside companies because it lacks context and cannot access internal systems securely. AI Enterprise Platform solves that by deploying — each expert in its own operational area.

What It Does

Instead of one generic chatbot, the platform orchestrates multiple agents specializing in HR, Finance, and Documentation. They operate independently, respect security constraints, and collaborate through a unified interface.


A Real Use Case


“Who can take on this new Python project?”
The HR Agent reviews employee skills, availability, and tenure →
The Document Agent extracts technical requirements from project files →
The system returns a precise, context-aware recommendation — instantly.


Why It Stands Out

  • A thoughtful answer to AI “hallucination through ignorance”

  • Practical deployment model for business environments

  • Strong architectural foundation designed for real-world integrations

How It Works

The Enterprise AI Assistant Platform is a production-ready, multi-agent AI system designed to streamline enterprise operations. It intelligently routes user queries to specialized agents, each optimized for specific domains:

  • HR Agent: Employee information, organizational structure, skills management, and HR policy queries

  • Analytics Agent: Business intelligence, data analysis, chart generation, and metric calculations

  • Document Agent: Agentic RAG-based document search, policy retrieval, and knowledge management

The platform features a sophisticated routing system that analyzes queries and directs them to the most appropriate agent, with fallback mechanisms and confidence scoring.


Component Flow

  1. User Query → Frontend sends request to FastAPI backend

  2. Root Chatbot → Receives query and invokes Agent Router

  3. Agent Router → Analyzes query using:

  • Keyword matching (domain-specific vocabularies)

  • Context awareness (conversation history)

  • Confidence scoring (threshold-based routing)

4. Specialized Agent → Processes query with domain expertise

5. Response → Returns structured response to frontend


Key Architectural Patterns

  • Microservices Architecture: Modular, independently deployable agents

  • Intelligent Routing: Dynamic query routing with fallback strategies

  • Agentic RAG (Retrieval-Augmented Generation): Document agent uses vector search for accurate responses

  • Observability: Integrated tracing with Opik for monitoring and debugging

  • Guardrails: AWS Bedrock Guardrails for content safety and compliance

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