Services
I help teams ship custom AI as a contractor — grounded in your data, with context engineering, guardrails, and deployment built in from day one.
Why chatbots
A chatbot isn’t a gimmick or a generic ChatGPT wrapper. It’s an assistant built on your documents, your policies, your product — that answers in seconds, cites where it found the answer, and knows when to say “I don’t know.” The useful ones are grounded, tested, and deployed — not demoed once and forgotten.
Policies, manuals, tickets, Confluence pages, PDFs. Your team knows the knowledge is there. Finding it in time is another story.
Your best people become human search engines — interrupted, repeating themselves, doing work that doesn’t need a human.
Tribal knowledge lives in heads and scattered docs. Onboarding means asking around and hoping someone remembers.
Real stories
Before
Czech teachers needed teaching methods and materials buried across millions of articles and internal resources. Searching took longer than preparing the lesson.
After
An assistant that searches 8 million articles in seconds — with sources, in plain language. 3,000 schools adopted it. AI Awards 2024. An estimated 11+ years of manual work saved for educators.
60,000 users
Before
A physician spent decades researching type 2 diabetes and obesity. The evidence existed — in papers, talks, and notebooks — but reached only the patients in her office.
After
A platform and AI assistant grounded in her research, helping far more people than one clinic ever could. Proof that the right bot isn’t about tech — it’s about getting knowledge to the people who need it.
Family project
That’s the pattern: knowledge your organization already has, delivered to the people who need it — without another meeting, another search, or another “who do I ask about this?” If that sounds like your problem, let’s talk.
What I build
Autonomous systems that plan, route, and execute — from internal workflow bots to customer-facing assistants with guardrails and evals built in.
Retrieval pipelines at scale — hybrid dense-sparse search, chunking strategies, citation, and the eval loops that keep answers honest in production.
Web mining with Playwright, structured pipelines, and clean hand-offs into your knowledge base — the data layer your bot actually needs.
Who I work with
Typical engagement
30 min · free
You describe the problem, I ask the hard questions. We leave knowing whether I am the right fit and what a first slice could look like.
2–4 weeks
A thin vertical slice with real retrieval, citation, and an eval harness — so we measure before we scale.
Ongoing
Guardrails, deployment, monitoring, and judge loops. You get a bot that improves, not one that drifts.
How I work
01
What should the bot know, who uses it, what does "good" look like? I define evals before writing prompts.
02
RAG pipeline, agent orchestration, guardrails — your stack (.NET or Python), your data.
03
Deployment, monitoring, judge loops in production. You get a bot that improves, not one that drifts.
FAQ
Or email directly: aneta.kahleova@gmail.com
