Useful AI systems, designed around the work they must improve.
We help teams move from an interesting model capability to a reliable product or internal workflow. The work begins with the decision, document or process that should become faster, clearer or more accurate.
Models are one part of the system. Data access, retrieval quality, tools, evaluation, human review, cost, latency and failure handling determine whether the feature is dependable.
Common applications
- Knowledge search and grounded question answering
- Document extraction, classification and review queues
- Drafting and transformation with structured output
- Operational assistants connected to approved business tools
- Customer-support triage and agent assistance
- Workflow automation across existing systems
Built for evaluation and control
We establish representative test cases, quality measures and safe fallbacks before scaling. Sensitive actions can require explicit approval, and system traces make it possible to understand why an output was produced.
Model-independent architecture
We keep prompts, retrieval, tools and evaluation separate enough to compare providers and improve the system without rewriting the product around one model API.