ai chatbots
Chatbots that actually know your business — grounded in your own content.
Chatbots built on your documentation, product data and policies using retrieval-augmented generation — so answers come from your content, not from a model's guesses. They can look things up in your systems, hand off to a human when needed, and tell you honestly when they don't know.
Sound familiar?
If any of these describe where you are right now, this is the right page.
The same questions arrive over and over and your team answers each one by hand.
Your documentation has the answers but nobody can find them.
You tried a generic chatbot and it confidently invented things about your product.
Prospects ask questions at 2am and get nothing until the next working day.
What you get
Concrete outputs, not a vague statement of work.
- A chatbot grounded in your own documents, site content, and product data (RAG)
- Embeddable web widget matched to your brand, plus WhatsApp or Slack where relevant
- Tool access so it can look up real records — orders, bookings, account status
- Source citations on answers, so users and your team can verify them
- Honest fallbacks and human handoff instead of confident invention
- An analytics dashboard showing what people ask and where the bot struggles
- A content pipeline so the bot stays current as your documentation changes
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How this project would run
Five stages, so you always know where things stand and what happens next.
Discover
We define what the bot must answer, what it must never attempt, and where it should hand off to a person.
Design
I audit your content, design the retrieval pipeline, and build an evaluation set of real questions to measure against.
Build
Built and tuned against that evaluation set, so quality is a number we track rather than a feeling.
Ship
Deployed to your site or channels, soft-launched to a subset of traffic first.
Support
Real conversations reveal gaps. I review them and tune retrieval and content in the weeks after launch.
Related work
Projects where I've done exactly this kind of build.
Agentic RAG Chatbot
A local agent-driven RAG system that combines LLM capabilities with tool integrations to deliver accurate, contextual AI responses without relying on external APIs.
- ▹5-step reasoning pipeline for transparent, auditable reasoning
- ▹Local AI system with tool integrations for contextual responses
- ▹No dependency on external APIs
Rubricate
rubricate.net
An agentic AI voice-interview and evaluation platform — the entire platform, built solo — that vets domain experts at scale with adaptive voice interviews backed by a full automated evaluation pipeline. The expert network behind Dataclap.
- ▹Agentic AI voice interviews that adapt to each candidate in real time
- ▹End-to-end automated evaluation pipeline with scoring rubrics
- ▹Automation workflows for sourcing, screening, and expert onboarding
AI Chatbots — questions
// next step
Need ai chatbots?
Book a 15-minute call and tell me what you're trying to build. You'll get a straight answer on whether I can help, what it would take, and roughly what it would cost.