AI
Products built around a model, not just a feature
For teams building AI-native products, we handle the full stack around the model — UX for uncertain/generative output, evaluation tooling, and the product engineering to ship it reliably.
Common challenges
- Designing UX for non-deterministic, generative output
- Keeping latency and cost under control at scale
- Turning a promising demo into a production-grade product
How we help
- LLM feature integration with evaluation and guardrails
- Vector database & retrieval architecture (RAG)
- Usage, cost and quality monitoring dashboards
Related work
AI case studies
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