Add AI to Your Product

We build AI features into your product — for your users. That means a chat assistant inside your SaaS, an AI search that understands your knowledge base, a copilot that drafts emails or answers questions, an agent that performs multi-step tasks, or AI-driven recommendations. Your users see and use the AI; we handle the integration, prompts, evaluation, and cost controls.

We pick the right model for the task. Anthropic Claude (Sonnet, Haiku) and OpenAI (GPT) for general reasoning and chat. Open-source models (Llama, Mistral) where the data is sensitive or you need on-device inference. Embedding models for RAG. We are model-agnostic and design so you can swap providers later.

Three layers. (1) Retrieval-augmented generation (RAG) so answers are grounded in your data. (2) Schema-validated outputs (JSON schemas, function calling) so structure is guaranteed. (3) Evaluation harnesses so we measure accuracy on representative examples before launch and as you iterate. We share these eval results with you.

We design for cost from day one: prompt caching, tiered model selection (cheap model first, expensive only when needed), aggressive context trimming, batching where possible, and per-tenant token budgets. We instrument every call so you can see cost per feature, per user, and per tenant.

Yes. We can build with EU-only data residency, zero-retention API keys, and on-prem or open-source models for sensitive workloads. We document the data flow for your DPIA and never use customer data to train external models.

A focused chat or RAG feature ships in 2 to 3 weeks. A full copilot with multi-step agents and proper evaluation takes 4 to 8 weeks. We usually start with a 1-week prototype so you can demo it before committing to a full build.