AI CHATBOT ON DOCUMENTS
Chatbot on your data — deployed in 2–4 weeks
RAG-based chatbot that answers questions from your company documents. No hallucinations — every answer has a source. Integrates with Confluence, Google Drive, SharePoint. Available cloud or on-premise.
Key Features
RAG on company documents (PDF, Word, Confluence, Drive)
Source citations — no hallucinations
Admin panel for knowledge base management
Cloud or on-premise (Private LLM)
How We Work Together
A proven methodology that delivers results
Discovery
We start with understanding your business, challenges, and goals through workshops and interviews.
Design
Together we design the solution architecture and create a detailed implementation plan.
Deliver
Iterative implementation with regular demos and feedback loops to ensure alignment.
Support
Post-launch support, knowledge transfer, and ongoing optimization recommendations.
Use Cases
- Q&A on company documents
- Search in policies and regulations
- Contract analysis and due diligence
- Knowledge base for support teams
Ideal For
- Regulated industries (insurance, fintech, legal)
- Knowledge workers with large document volumes
- Organizations with distributed knowledge bases
Not Ideal For
- Companies without structured documents
- Real-time data (stock exchange, IoT)
- Teams under 5 people without chatbot needs
Related Case Studies
RAG Document Processing System
At Insly, I led development of a RAG (Retrieval-Augmented Generation) system that gives insurance brokers fast, context-aware answers about policy details. The system combines traditional search with vector embeddings to handle complex queries across 23 different insurance providers.
Challenge
Insurance brokers needed to quickly find relevant information across thousands of policy documents from 23 different insurers, each with unique formats and terminology.
Microservices Migration
CloudAcademy needed to migrate their content authorization service from Kotlin to Go as part of a broader standardization effort. I led this migration while ensuring zero downtime and creating new microservices following DDD patterns.
Challenge
Legacy Kotlin service had performance bottlenecks and was difficult to maintain. Team needed to standardize on Go for better consistency across microservices.
Ready to Transform Your Business?
Let's discuss how I can help you achieve your goals. The first consultation is free.