Custom AI Applications

We ground models in your own data with retrieval (RAG) so responses are based on real sources, add evaluation and guardrails, and measure accuracy against test cases before anything ships. Where it helps, answers cite the source so users can verify them — accuracy you can audit, not just hope for.

No. Many high-value features work immediately with LLMs and your existing documents, tickets, and workflows — no training data required. Where a custom or fine-tuned model genuinely adds value, we'll tell you exactly what data is needed and whether the payoff justifies it.

Yes. We build AI features as a clean, well-documented part of your current stack — proper APIs, sensible boundaries, and your design system — so it feels native to the product rather than a bolted-on widget.

We're model-agnostic and choose based on the job, your accuracy needs, data-privacy requirements, and cost — frontier models like Claude and GPT, open models you can self-host, or a mix. You're never locked to a single vendor, and we can swap models as the landscape changes.

Your data stays within boundaries you control. We support private deployments, scope what the application can access, avoid training third-party models on your data, and design to the compliance requirements your industry demands.