InsightFlow
AI Business Intelligence Agent — a production-grade, multi-step AI
agent that connects to and takes action across real business apps.
A user asks, in plain language (English, Hindi, or Telugu — text or
voice): "Why did sales drop in Hyderabad last week? Tell the team."
InsightFlow then:
- Reads the data from Google Sheets
- Syncs it and runs deterministic analysis (DuckDB/Pandas — the LLM
never does the math itself) with Sarvam-105B reasoning over the
verified numbers via LangGraph + LangChain
- Drafts a report and waits for human approval before doing anything
- Writes the report to Notion
- Posts an alert to Slack
Every step is persisted and resumable — a crash mid-run picks back up
from its last checkpoint, not from scratch.
Why this project
Most "chat with your data" demos stop at answering a question. InsightFlow
is built as a real product: authenticated multi-tenant SaaS (Clerk),
billed subscriptions (Razorpay), a durable agent (LangGraph checkpoints
on Postgres), and actions across three external systems gated behind
explicit human approval — not a notebook, a running service.
Tech stack
| Layer | Choice |
|---|
| Agent orchestration | LangGraph + LangChain |
| LLM | Sarvam-105B (langchain-sarvam) |
| Backend API | FastAPI (async), SQLAlchemy 2 |
| Database | Neon Postgres (+ pgvector later) |
| Queue / cache | Redis + Celery |
| Auth | Clerk |
| Billing | Razorpay Subscriptions |
| Frontend | Next.js + TypeScript, installable PWA |
| Deploy | Render (stage 1) → Coolify on a VPS (stage 2) |
Repository layout
backend/ FastAPI + LangGraph backend — see backend/README.md
frontend/ Next.js + React PWA — added in Phase 1 (not yet created)
Status
This project is being built in phases — see the roadmap for the full
architecture, phase checklists, and what's done vs. planned. Phase 0
(backend foundations: app structure, Neon wiring, health checks, CI,
Docker) is complete; Phase 1 (Clerk auth + multi-tenancy) is next.
Getting started (backend)
cd backend
cp .env.example .env # fill in your Neon connection strings
uv sync
uv run alembic upgrade head
uv run uvicorn app.main:app --reload # Linux/macOS/WSL
uv run python -m app.dev_server # Windows
Full instructions: backend/README.md.
License
Not yet decided / all rights reserved for now.
