AI Chatbots Built with Flowise — Deployed in Days

Flowise provides a visual interface for LangChain that dramatically speeds up development — you can prototype and iterate on chatbot flows without writing code for every chain. We then add custom nodes and code for anything beyond the visual builder. It's the best of both worlds: speed and flexibility.

Yes — this is one of Flowise's key advantages. We deploy Flowise as a Docker container on your cloud provider or on-premise servers. All conversation data, documents, and vector embeddings stay in your infrastructure. If you use local LLMs via Ollama, even the AI model runs on your hardware.

We implement retrieval-augmented generation (RAG) to ground answers in your approved content, configure the model to say "I don't know" for out-of-scope questions, add a confidence threshold below which the bot escalates to a human, and set up conversation review dashboards so you can catch and fix problematic answers.

Yes — we integrate human-in-the-loop escalation via your preferred live chat platform (Intercom, Zendesk, Crisp, etc.). The bot detects escalation triggers (user frustration, complex questions, specific keywords) and seamlessly transfers the conversation with full context to a human agent.