AI features and products built on your data, not a generic demo.
The problem
Most "AI features" are a thin prompt wrapper that breaks the moment real users touch it with real data.
Our approach
We build AI systems grounded in your actual data and workflows — evaluated, monitored, and engineered to fail gracefully.
Capabilities
Click a card, or use the arrows →
LLM-powered features & copilots
Assistants and copilots embedded in your product, scoped to what they can reliably do well instead of promising to do everything.
What this looks like when it's working
A feature that handles real, messy input, not just the demo case.
Answers your team can trust because they're grounded in your actual data.
A system that fails safely instead of confidently making things up.
Deliverables
Technology
Every engagement follows the same five-stage process, regardless of service.
See how we work →Related concept work
Common questions
Whichever fits the problem and budget — we stay model-agnostic and design systems that can swap providers as the field moves.
Before launch, against a real evaluation set built from actual cases. After launch, against usage data and a monitored feedback loop — not just "it seemed fine in testing."
We design for it directly — grounding answers in real data (RAG), constraining what the system is allowed to claim, and building a review step in wherever the cost of being wrong is high.
More in Intelligence
Intelligence
Explore an AI build
Tell us what you want AI to actually do in your product or business.