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Overview

Summary

AI Operational Intelligence Prototype — a technical PoC / working prototype of controlled LLM execution for evidence-backed analytics.

The original working name was AI Operational Intelligence Platform / Executive Decision Intelligence. That name described the intended product direction, not the maturity of what was built.

The prototype explores how an executive analytics assistant could be built. A user asks an analytical question in a chat-like UI; the backend runs a controlled execution flow over prepared synthetic data. The LLM is intended to act inside a backend-mediated tool environment, not as a free-form chatbot with arbitrary data access.

This is not a production platform and not a complete multi-turn decision-support product. It is an experimental enterprise AI architecture prototype that validated a bounded execution idea.

What was prototyped

  • chat-like UI based on Open WebUI;
  • experimental LangGraph-based execution flow;
  • backend tools for accessing prepared synthetic data;
  • initial tool registry / tool description concept;
  • synthetic financial and cross-functional management scenarios;
  • single-turn analytical requests;
  • evidence-backed response pattern;
  • basic execution trace / run details;
  • architectural documentation and future direction.

Technology Stack

Layer PoC choice Role
Chat-like UI Open WebUI Temporary demo interface
Execution flow FastAPI + LangGraph Experimental single-request diagnostic flow
Tool execution FastAPI tool-server Controlled backend tools, validation, structured output
Structured data PostgreSQL Synthetic finance, delivery, ITSM, PMO, meetings data
Document store MinIO + Qdrant Document evidence direction for RAG
Runtime/cache Redis Lab runtime support
LLM OpenAI-compatible API Planning and synthesis; not a source of truth
Infra Docker Compose Reproducible lab stand

Architecture patterns explored: Tool Gateway, Tool Registry concept, prototype playbook routing, RAG direction, run trace, evidence trail.

Development approach: AI-assisted prototyping, synthetic data generation, scenario-driven PoC validation.