Production Deployment — Live at chatbot.datawebify.com

Multi-Agent AI
Chatbot System

A production-ready multi-agent platform that connects to any external business API, answers questions from your documents with source citations, and delivers everything through a turn-by-turn chat interface with full session memory.

▶ Live Demo 📄 API Docs </> View Source ● Health Check

01 — The Business Case

Problem. Solution. ROI.

⚠ The Problem

Enterprise clients need AI chatbots that connect to their existing business data, not generic LLM wrappers. They need RAG over their own documents, live data from their APIs, and a proper chat interface with memory — all in one production system.

External API integrationCustom code per integration

Document Q&A with citationsManual lookup

Chat interfaceGoal-submission form only

Session memoryNo context retention

✓ The Solution

A unified multi-agent platform closing all three gaps: configurable external API connectors, a full end-to-end RAG pipeline, and a polished chat UI with session memory — orchestrated by LangGraph and deployed to production in one system.

External API integrationAny API, zero code changes

Document Q&A with citationsPDF, DOCX, URL — cited answers

Chat interfaceFull turn-by-turn UI

Session memoryMulti-turn conversation memory

02 — What Was Built

Three Core Capabilities

Phase A

External API Integration Agent

Connects to any external business API with zero code changes. Auth methods: Bearer token, API key, Basic auth, None. All config via environment variables. Includes inbound webhook receiver for event-driven ingestion. Live connectors: wttr.in weather and RestCountries.

Phase B

Full RAG Pipeline

End-to-end document ingestion to cited answer generation. Ingests PDF, DOCX, and URLs. Semantic chunking with overlap, OpenAI text-embedding-3-small embeddings, Pinecone vector store with hybrid search and reranking. Every answer includes source document and relevance score.

Phase C

Conversational Chat Interface

Turn-by-turn chat UI in Next.js 14. Message bubble layout, session memory for multi-turn follow-up questions, chat history sidebar with persistent sessions, and live WebSocket execution feed as collapsible side panel during agent runs.

03 — System Design

Agent Architecture

💬

Chat UI

Next.js 14 + WebSocket

🌐

Orchestrator

LangGraph + GPT-4o

🔗

API Agent

REST + Webhooks

📐

RAG Agent

Pinecone + Reranker

🔍

Web Search

Tavily API

✅

Supervisor

Claude API validation

04 — Technology

Tech Stack

🌐

LangGraph

Multi-Agent Orchestration

🤖

GPT-4o + Claude API

Primary LLM + Fallback

📐

Pinecone

Vector Store + Hybrid Search

⚡

FastAPI + Python 3.12

Backend + WebSockets

💻

Next.js 14 + Tailwind

Chat UI Frontend

🚀

Railway + Vercel

Backend + Frontend Deploy

📄

Supabase + pgvector

Database + Session Memory

🔍

Tavily API

Real-Time Web Search

🚧

Docker + MCP

Containerization + Protocol

05 — Performance

Business Metrics

Metric	Before	After	Change
External API Connection	Custom code per integration	Config via env vars, zero code	100% faster
Document Q&A Response	Manual search, minutes	Under 3 seconds, cited	99% faster
Chat Context Retention	None — single-turn only	Full multi-turn session memory	Full memory
Agent Coordination	Single-agent, no routing	8 specialists, LangGraph routing	8x capability
Deployment	Local only	Railway + Vercel, auto-deploy	Production ready

06 — Integration

REST API

GET/healthSystem health check — returns status and environment

POST/api/executeSubmit a goal for full multi-agent execution

POST/api/v1/chatTurn-by-turn chat with session memory

POST/api/v1/ingest/fileUpload PDF or DOCX for RAG ingestion

POST/api/v1/ingest/urlIngest any public URL into the knowledge base

GET/api/connectors/weatherLive weather data via wttr.in connector

GET/api/connectors/countriesCountry intelligence via RestCountries connector

POST/api/webhook/{source}Inbound webhook receiver for event-driven data

WS/ws/execute/{session_id}Live WebSocket execution step feed

07 — Applications

Who Needs This

🏢

SaaS Platforms

Embed an AI assistant that connects to your product's API and answers questions from your help docs — deployed in days, not months.

📈

Financial Services

Query live market data and internal policy documents in the same conversation. Source-cited answers for every compliance query.

🛒

E-commerce

Connect to inventory APIs, answer product questions from spec sheets, and handle multi-turn customer conversations at scale.

⚖

Legal & Compliance

Ingest contracts and regulations, connect to case management APIs, and deliver cited answers across multi-turn research sessions.

🏥

Healthcare

Connect to EHR APIs, answer protocol questions from clinical guidelines, and maintain full context across a consultation session.

🏭

Enterprise Operations

Wire together ERP, CRM, and internal knowledge bases into a single chat interface for the entire operations team.

Ready to Deploy

Build This for Your Business

Typical engagement: $3,500 to $7,000. Connects to your existing APIs and documents on day one. Full source code, Docker deployment, and documentation included.

▶ Live Demo </> GitHub Repo ← All Projects

🌐 datawebify.com

👤 Muhammad Umair — Agentic AI Specialist

📄 github.com/umair801

Multi-Agent AI Chatbot System