Multi-Agent Orchestration · Enterprise Analytics2025

Enterprise Agentic Analytics Platform

A governed analytics platform that translates business questions into KPI planning, semantic retrieval, SQL generation, Microsoft Fabric execution, validation, visualization, and decision-ready insights.

FastAPIAzure OpenAIMicrosoft FabricAzure AI SearchRedisSQL
Project summary

Impact

Self-service analytics

KPI retrieval, SQL execution, validation, and insight generation within one governed workflow

Hiring signal

What this proves

Multi-agent orchestration, Python backend ownership, analytical reliability, Microsoft Fabric integration, and typed response design.

My role

Ownership

Lead developer · FastAPI backend, agent orchestration, SQL generation, validation workflows, Redis state management, Fabric SQL integration, and response contracts

Status

Enterprise implementation case study

An interactive trace is available.

The problem

What needed to change

Business users relied on static dashboards and ad hoc BI support for questions that fell outside predefined reports. Each new request required manual SQL development, report changes, or a separate analytical cycle before a reliable answer could be delivered.

My approach

How I built it

The platform uses a FastAPI orchestration layer to coordinate intent classification, query decomposition, KPI planning, metadata retrieval, semantic enrichment, SQL generation, Microsoft Fabric SQL Endpoint execution, result validation, chart construction, and insight synthesis. Each stage exposes a defined contract, allowing failures to be isolated, retried, and reported transparently.

Architecture judgment

Why this design

A single text-to-SQL prompt is too fragile for an enterprise KPI catalog. Separating planning, retrieval, execution, validation, and response generation creates explicit control points, safer retry boundaries, and a traceable analytical output.

Architecture

High-level system design

The complete execution path, service boundaries, data stores, security controls, validation stages, and operational telemetry.

Implementation

Key components

  • FastAPI analytics API with typed request and response contracts
  • Redis-backed history, metadata, and warm connections
  • Focused agents for intent, KPI planning, SQL, validation, and insight
  • Azure AI Search retrieval over KPI and table metadata
  • Microsoft Fabric SQL Endpoint execution
  • Validation and refinement loop before the final answer

Technology

Tech stack

Backend

PythonFastAPIAsyncIOPydantic

Agentic AI

Azure OpenAILangGraphRAGMulti-Agent Orchestration

Data

Microsoft FabricFabric SQL EndpointSQLDelta Lake

State & Retrieval

RedisAzure AI SearchVector Search

Interactive trace

See the workflow run

analytics platform · multi-agent execution trace

Run the trace to see the main workflow stages.