We build software with AI at its core: features powered by large language models, AI models integrated into your existing systems, and models trained or fine-tuned on your own data. It sits on the same engineering we use for every product, so it is tested, secure and maintainable.
Chat, search, summarisation and assistants built into your product, with guardrails for your use case.
Connect AI models to your data, APIs and workflows instead of running them as a separate tool.
Adapt models to your domain and data when an off-the-shelf model is not accurate enough.
Backend, frontend and infrastructure built by the same team, not a bolted-on prototype.
Access control and data handling planned in from the start, especially for sensitive data.
Our SET program includes an AI Engineering track, so the skills are built in-house.
Claude, Gemini, DeepSeek, GLM
Claude Code, Claude Desktop, Codex, Cursor, Kiro, Zed
Figma AI, Postman AI
Hermes Agent and OpenClaw in Discord and Slack
Obsidian as a shared second brain
How we take an AI idea from prototype to production.
1
Pick the problem where AI adds real value, and agree how success is measured.
2
Test models and prompts on your data before committing to a full build.
3
Build the feature into your product with proper testing and monitoring.
4
Release, watch quality and cost, and keep improving the model and prompts.