AI chatbot
built on
precise logic
Haagse Kennis designs and develops AI chatbots for organizations that need structured, reliable conversational systems - not general-purpose tools adapted after the fact. Every system we build starts from a defined problem, not a template.
Where the work
actually starts
Most chatbot projects fail at the specification stage - requirements are vague, edge cases are ignored, and the resulting system handles only the 3 or 4 scenarios the team remembered to test. At Haagse Kennis, we treat conversation design as a formal discipline, closer to systems architecture than to UX writing.
Our team has worked across automated trading bots, algo trading bot interfaces, and quant trading data pipelines - environments where ambiguity costs real money. That background shapes how we think about AI chatbot reliability: every decision point in a conversation needs a defined outcome, not a fallback phrase.
"A chatbot that handles 91% of cases cleanly is not a success - it is a system with 9% unresolved failure modes waiting to surface."
- Haagse Kennis internal design standard
Remote-first, structured by design
Working with clients across 14 time zones has pushed us to build clear async-first processes. Deliverables are documented, decisions are recorded, and nothing depends on a single synchronous call.
Specialists, not generalists
Each project draws from a fixed core of practitioners with defined roles. No one person covers automated trading bots, crypto bot architecture, and conversation design simultaneously - depth matters more than breadth.
Designs the decision logic and state management behind each chatbot system. Previously worked on quant trading signal pipelines for 7 years.
Maps dialogue flows and edge-case handling. Brings a background in structured linguistics and prior work on crypto automation interfaces.
Handles API design, webhook architecture, and backtesting harnesses that validate bot behavior before production release.
Runs structured test suites across all conversation paths. Focuses on failure mode documentation and algo trading bot stress scenarios.