Enterprise AI Product

Meet IndiBot
Your AI Chatbot,
Your Knowledge.

An enterprise-grade AI chatbot that learns from your documents, policies, and data. Built on Google Gemini, LangChain, and RAG — deployed in days, not months.

Google Gemini LangChain Vector RAG GDPR Ready 22+ Languages
IndiBot AI Chatbot Interface
72h
Average Deploy Time
98%
Query Accuracy (RAG)
22+
Languages Supported
60%
Support Cost Reduction
CAPABILITIES

What IndiBot Can Do

A full-stack AI assistant engineered for enterprise — not just a widget, but a knowledge layer across your entire business.

RAG-Powered Knowledge Base

Ground every response in your actual documents — PDFs, Word files, URLs, databases. No hallucinations. Answers sourced from your verified content with citations.

Multi-Turn Conversation

Context-aware dialogue that remembers the full conversation thread. Handles follow-up questions, clarifications, and complex multi-step queries naturally.

Multilingual Support

Responds in 22+ languages including Hindi, Tamil, Telugu, Bengali, and all major Indian regional languages via Bhashini integration. One bot for every user.

Smart Lead Capture

Intelligently collects visitor information — name, email, intent — at the right moment in the conversation, with GDPR-compliant consent flows built in.

Agentic Task Execution

Goes beyond Q&A — can book appointments, fill CRM records, trigger workflows, search internal systems, and hand off to human agents seamlessly.

Analytics & Reporting

Full conversation analytics dashboard: resolution rates, unanswered queries, CSAT scores, topic distribution, and peak usage patterns for continuous improvement.

Enterprise Security

Role-based access control, encrypted vector storage, data residency options, SOC 2 aligned logging, and on-premise deployment available for sensitive industries.

White-Label Ready

Full custom branding — your logo, colors, domain, and tone-of-voice. Embed as a widget, serve from a standalone URL, or integrate into your existing app.

Response Caching

Semantic caching layer reduces repeated API calls by up to 70%, cutting operational costs significantly while maintaining sub-second response times at scale.

TECH STACK

Built on Best-in-Class Technology

Every layer of IndiBot is chosen for enterprise reliability, developer transparency, and AI accuracy — from the LLM core to the vector store.

IndiBot Tech Stack Architecture
1
Frontend Widget Layer
Lightweight React-based floating chat widget (< 20 KB gzipped). Embeds via a single script tag on any website or app. Supports dark/light modes and custom themes.
ReactJavaScriptWebSocketCSS Variables
2
API & Conversation Engine
Flask REST API handles session management, rate limiting, authentication, and lead capture. Stateless design with Redis session store for horizontal scaling.
PythonFlaskRedisJWT AuthREST API
3
LangChain Orchestration
LangChain manages prompt templates, chain-of-thought reasoning, tool calling, memory buffers, and RAG retrieval pipelines. Gives full control over AI behavior without touching the model API.
LangChainPrompt TemplatesReAct AgentsConversationBufferMemory
4
Google Gemini LLM Core
Powered by Google Gemini 1.5 Pro / Flash via Vertex AI. 1M token context window enables processing of entire policy documents, legal contracts, and knowledge repositories in a single pass.
Gemini 1.5 ProVertex AIFunction CallingMultimodal
5
Vector Database (RAG Store)
Documents chunked and embedded into a vector database. Semantic similarity search retrieves the most relevant context before each AI response — grounding answers in your data, not guesses.
ChromaDB / Pineconetext-embedding-004FAISSSemantic Search
6
Caching & Cost Control
Two-level caching: SQLite for exact-match queries and in-memory semantic cache for near-duplicate queries. Reduces Gemini API costs by 60-70% at production scale.
SQLite CacheSemantic CacheLangChain CacheCost Analytics
HOW RAG WORKS

Retrieval-Augmented Generation — Your Bot, Your Data

Standard chatbots hallucinate. IndiBot doesn't. RAG (Retrieval-Augmented Generation) ensures every answer is drawn directly from documents you've approved — with a traceable source reference.

1
Document Ingestion

Upload PDFs, Word docs, URLs, SharePoint pages, or connect databases. Our pipeline extracts, cleans, and chunks content into optimal segments for retrieval.

2
Vector Embedding

Each document chunk is converted into a high-dimensional vector using Google's text-embedding-004 model and stored in a vector database with metadata.

3
Semantic Retrieval

When a user asks a question, the query is embedded and a cosine similarity search finds the top-K most semantically relevant document chunks — in milliseconds.

4
Grounded Generation

Retrieved chunks are injected into a carefully engineered prompt. Gemini generates an answer strictly grounded in those chunks — with citations, confidence scores, and fallback handling.

5
Continuous Learning

Unanswered or low-confidence queries are logged for your review. Update your knowledge base — changes reflect live within minutes, no retraining needed.

RAG Architecture Visualization
98%
Answer Accuracy
< 1s
Avg. Retrieval Time
0
Hallucinations (with RAG)
1M+
Token Context Window
INTEGRATIONS

Connects to Your Existing Stack

IndiBot integrates with the tools your team already uses — no complex middleware or custom development required.

WhatsApp Telegram Slack MS Teams Gmail Salesforce HubSpot SharePoint Google Drive AWS S3 PostgreSQL Voice / IVR WordPress Shopify Custom API
Website Embed

Drop one script tag on any site. Zero CMS configuration. Works with WordPress, Webflow, React, or plain HTML.

REST API

Full REST API for programmatic integration into your mobile app, backend, or internal tool. OpenAPI spec included.

On-Premise / Private Cloud

Deploy entirely within your VPC or on-premise servers. All data stays in your environment. Available for Enterprise plans.

DEPLOYMENT

IndiBot vs Generic Chatbots

Feature IndiBot Generic Chatbot ChatGPT Plugin
RAG on your documents
On-premise deployment
Custom branding / white-label
Indian language support (22+)
Agentic task execution
Lead capture + CRM sync
Analytics dashboard
Semantic response caching
Data stays in your environment
PRICING

Simple, Transparent Pricing

All plans include setup, onboarding, and 60 days of free support. No hidden fees.

STARTER
₹29,999
One-time setup + ₹4,999/mo
Up to 5 knowledge base documents
Website embed widget
English + 1 regional language
5,000 messages / month
Lead capture & email alerts
Basic analytics dashboard
RAG custom documents
White-label / custom domain
Get Started
PROFESSIONAL
₹79,999
One-time setup + ₹11,999/mo
Up to 100 RAG documents
Website + WhatsApp + API
All 22+ Indian languages
25,000 messages / month
CRM integration (HubSpot / SF)
Advanced analytics + CSAT
Custom branding
Agentic task actions
Get Started
ENTERPRISE
Custom
Tailored to your scale
Unlimited RAG documents
All channels (voice, email, chat)
Unlimited messages
On-premise / VPC deployment
Full white-label
SLA + dedicated support
Fine-tuning on proprietary data
VAPT & compliance support
Talk to Sales

Ready to Deploy IndiBot?

Get a personalized demo using your own documents. We'll show you exactly how IndiBot would answer questions about your products, policies, or services — in under an hour.