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Intelligence engineered into the product, not bolted on.
We connect models to useful interfaces, governed data, and measurable workflows so AI has a clear job inside the product.
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Good engineering makes change easier.
AI features need to earn trust. We design around the task, ground responses in relevant context, and build evaluation and human review into the workflow where they matter.
Designed around
the real work.
Scope follows your users, existing systems, and delivery constraints. These are common ways this capability takes shape.
- LLM product integrations and structured outputs
- Retrieval-augmented generation and knowledge search
- Task-oriented AI agents and tool workflows
- Semantic search and vector retrieval
- Human review, permissions, and audit trails
- Evaluation, guardrails, and usage monitoring
Make progress
deliberately.
We adapt the sequence to the project. The work stays visible, decisions stay grounded, and quality checks are part of delivery.
- 01
Choose a bounded task and define a useful quality measure.
- 02
Connect models to governed context and deterministic tools.
- 03
Test against representative cases and add review paths.
LLM APIs
Vector databases
TypeScript