Mindly turns sensitive business corpora into reliable conversational assistants without locking the client into a single model or provider.

I framed the architecture and arbitrated the technical choices with the AI and data teams. The foundation covers ingestion, processing, vectorization, semantic search, streaming generation and conversation history. The multi-tenant architecture enforces strict isolation, secure authentication, rate limiting and traceability for sensitive actions. It stays agnostic to the LLM provider and can run locally.

The client gets a reusable, scalable and controlled platform, able to return near-instant answers without exposing its data to an external service.