About the service
I design and build self-hosted conversational AI on Rasa — a smart assistant you truly own: code, models, and user conversations stay on your infrastructure. I deliver support chatbots, internal helpdesk agents, lead qualification bots, and voice assistants end-to-end. I handle the entire pipeline: intent and entity recognition (NLU), dialogue management, forms for data collection, custom actions, and clean integrations with your CRM, databases, and messengers.
Work starts with your real conversations. I analyze what users actually mean, identify relevant entities, and train an NLU model that handles rephrasing, typos, and mixed phrasing. Then I build robust dialogue policies with Rasa rules and stories, so the assistant stays on track, asks clarifying questions through forms, and gracefully handles out-of-scope requests. A custom action server connects the bot to your APIs — it checks orders, books slots, and triggers business processes in real time.
You get documented, testable, containerized software: no vendor lock-in, no per-message fees, no data leaks. I set up test stories, CI checks, and retraining procedures so the assistant keeps improving after launch. What you receive:
— Trained NLU pipeline for your intents and entities;
— Dialogue policies, forms, and fallback handling;
— Custom action server connected to your systems;
— Containerized build with tests and documentation.
Work starts with your real conversations. I analyze what users actually mean, identify relevant entities, and train an NLU model that handles rephrasing, typos, and mixed phrasing. Then I build robust dialogue policies with Rasa rules and stories, so the assistant stays on track, asks clarifying questions through forms, and gracefully handles out-of-scope requests. A custom action server connects the bot to your APIs — it checks orders, books slots, and triggers business processes in real time.
You get documented, testable, containerized software: no vendor lock-in, no per-message fees, no data leaks. I set up test stories, CI checks, and retraining procedures so the assistant keeps improving after launch. What you receive:
— Trained NLU pipeline for your intents and entities;
— Dialogue policies, forms, and fallback handling;
— Custom action server connected to your systems;
— Containerized build with tests and documentation.
