Context

As AI adoption grows, organizations face risks from relying on a single vendor for AI models and transmitting sensitive data through third-party services. To mitigate these risks, we designed a custom, LLM-agnostic chatbot solution that ensures data privacy and eliminates third-party integrations.

Deliverables

I implemented a ChatGPT-like interface based on Open Source with a robust React UI, allowing users to interact with various LLM agents, each equipped with RAG (retrieval-augmented generation) knowledge bases and agentic tools for real-time data access. The NodeJS - Express backend connects to multiple LLMs, making it agnostic to specific AI providers. The self-contained, dockerized deployment ensures data privacy and eliminates external dependencies.

Results

The project delivered the following benefits:

• Enhanced Data Security: No third-party integrations or external AI providers, safeguarding chat interactions and proprietary data.

• Flexibility and Freedom: LLM-agnostic design allows the client to use any LLM, avoiding vendor lock-in and enabling adaptability to future AI developments.

• Real-time Data Access: RAG knowledge bases and agentic tools provide instant access to relevant information, enhancing the chat experience.

• Predictable Costs: No reliance on external AI services with usage-based pricing, providing more predictable operational costs.

• Improved Reliability: Simplified deployment and reduced reliance on external systems, resulting in fewer points of failure and greater overall reliability.

This project addressed key security concerns, providing a flexible, scalable, and future-proof AI chatbot solution.

Interested in this solution?