AI Application Development for Real Products
Assistants, document search, workflow agents and LLM features — integrated safely, with guardrails and human review.
AI is easy to demo and hard to ship responsibly. Without grounding, guardrails and evaluation, AI features become unreliable and expensive — and can erode trust instead of building it.
We build AI features that ship — support assistants, document search, workflow agents, voice interfaces and LLM integration — wired into your product with sensible guardrails and human review where it matters.
We focus on reliability and cost control: grounded, retrieval-augmented answers over your own data, prompt and context management, evaluation and clean fallbacks — so AI genuinely helps users instead of becoming a liability.
Who it's for
What's included
Built With
How we work
Use-case scoping
We identify where AI adds real value — and where it does not.
Prototype
A focused prototype to validate quality, latency and cost early.
Integrate
Production integration with guardrails, logging and evaluation.
Iterate
Ongoing tuning based on real usage and measured quality.
Security and reliability
We keep humans in the loop for sensitive actions, ground responses in your data, log and evaluate outputs, and never promise unattended autonomous behaviour we cannot verify.
Frequently asked
Which AI models do you use?
We work with leading providers such as Claude and OpenAI, choosing the best fit for quality, latency and cost.
Can you use our own data?
Yes. We build RAG pipelines and vector search so answers are grounded in your documents and data.
Do you build fully autonomous agents?
We build practical agents with guardrails and human review. We do not promise unsupervised autonomy we cannot make reliable.
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