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05Artificial Intelligence
We design intelligent systems around the product and the operation they serve — the data they can trust, the tools they may use, the actions that need a human to confirm. The result is AI that is useful in production, not only impressive in a demo.
Conversational and voice interfaces grounded in your real data, with transparent tool use.
Multi-step agents with scoped tools, explicit confirmations and auditable actions.
Model selection, prompting, retrieval, streaming and cost control across providers.
Detection, tracking and gesture interfaces running in the browser or on the server.
Document processing, classification and extraction pipelines with human review where it matters.
Routing, fallbacks, evaluation and observability for systems built on several models.
Scope
Intelligence field · 3 systems
Hover or select a system to inspect it.
An assistant is only as reliable as the data it reads — sources and freshness are designed explicitly.
Tools are scoped, consequential actions require confirmation, and every call is observable.
Behaviour is measured against real tasks before and after every change.
Typical stack
AI assistants, agents, LLM integrations, retrieval over your own data, computer vision and document automation — designed around your product and operations rather than as a bolt-on feature.
By grounding it in your real data sources, giving it narrow, validated tools, and making it say when information is unavailable. Answers show which sources were used.
Yes, with explicit boundaries: tools are scoped to the task, and any consequential action is proposed to a person and executed only after confirmation.