A chat box on the side
AI added as a separate panel never reaches the places where users actually work.
AI-native applications
We design and build applications where AI is part of the product from the first screen, and where your users keep control of their data.
The problem
AI added as a separate panel never reaches the places where users actually work.
User data flows to models no one reviewed, and trust is lost when it surfaces.
Without measures and records, no one can tell if the AI is helping.
Our approach
Summaries, drafts, sorting, and suggestions placed where users already work.
MCP tools so outside assistants can work with your app, with consent and approval.
Data minimisation, clear consent, and model choices that match your obligations.
Applications your customers can run on their own servers or use on yours.
What we ship ourselves
Our own products are AI-native: Mail summarises and suggests replies, Business has an agent in its dashboard, SourceAnt reviews pull requests, and Chatbrush designs through conversation.
See our products
How it works
We shape the product around the tasks AI should take on, and the data it may touch.
Senior engineers ship in short cycles with weekly demos.
We launch, monitor quality and cost, and keep improving with you.
Privacy and control
Questions
Yes. We start with the tasks where AI fits naturally and change only what those tasks need.
Whichever fits the task and your obligations: hosted providers, open-weight models on your servers, or a mix.
You do. We hand over code, infrastructure, and runbooks your team can run.
Start a conversation
An engineer replies within 24 hours with how we would approach it.