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Multi-tenant enterprise RAG chatbot

DocuChat

A multi-tenant RAG chatbot platform with WhatsApp, Telegram, live human handoff and an 18 KB embeddable widget.

Visit docuchat-murex.vercel.app ↗
  • RAG
  • Laravel 11
  • Vue 3
  • pgvector
  • Multi-LLM
DocuChat screenshot

Overview

DocuChat is a live multi-tenant RAG platform with Gemini / OpenAI / Claude failover and 768-dimension embeddings on Neon Postgres. Each tenant's knowledge base, conversations and channels are strictly isolated.

How it works

  1. 1PDF / crawler
  2. 2Chunk + embed (768-d)
  3. 3Tenant-scoped pgvector
  4. 4Vector cache
  5. 5Gemini / OpenAI / Claude
  6. 6Web · WhatsApp · Telegram

What I built

Hybrid ingestion

PDFs and a web crawler feed each tenant's knowledge base.

Semantic vector cache

Repeat questions are answered from a pgvector cache in under 15 ms.

Quality evals

Automated answer-quality evaluations and hallucination benchmarks.

Omnichannel

Telegram and WhatsApp channels, plus a live human-handoff inbox for conversations the bot shouldn't own.

Developer platform

REST APIs, HMAC-signed webhooks and an embeddable web widget under 18 KB.

Cost and reliability

Token cost and ROI tracked in rupees; multi-provider LLM fallback; 34/34 Pest test suites passing.

Engineering decisions

  • Isolate tenants at the query layer so no retrieval can cross a tenant boundary.
  • Fail over between three LLM providers so one provider's outage doesn't take customers' bots down.
  • Measure hallucination with automated evals instead of trusting spot checks.

Stack

Backend
Laravel 11, Pest
Frontend
Vue 3 (Inertia)
Data
Neon PostgreSQL + pgvector (768-d embeddings)
AI
Gemini, OpenAI, Claude with failover
Channels
Web widget, Telegram, WhatsApp, REST API, HMAC webhooks

Need something like this?

I can build a version of this for your product, your data and your stack.

Start a project