AI-native applications

Software built around AI, with privacy designed in.

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

Why bolted-on AI disappoints.

A chat box on the side

AI added as a separate panel never reaches the places where users actually work.

Privacy as an afterthought

User data flows to models no one reviewed, and trust is lost when it surfaces.

Nothing to steer by

Without measures and records, no one can tell if the AI is helping.

Our approach

What we build.

AI in the main flow

Summaries, drafts, sorting, and suggestions placed where users already work.

Tools agents can use

MCP tools so outside assistants can work with your app, with consent and approval.

Privacy by design

Data minimisation, clear consent, and model choices that match your obligations.

Self-host or cloud

Applications your customers can run on their own servers or use on yours.

What we ship ourselves

Desk, Business, SourceAnt, and Chatbrush.

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
WhileSmart Docs

How it works

Three steps, each one reviewable.

  1. Design

    We shape the product around the tasks AI should take on, and the data it may touch.

  2. Build

    Senior engineers ship in short cycles with weekly demos.

  3. Run

    We launch, monitor quality and cost, and keep improving with you.

Privacy and control

Your data, your rules.

  • Your data stays in systems you control, or in a region and provider you approve.
  • Assistants and agents act with the access of the person using them, never more.
  • Anything that sends, pays, or deletes waits for a person to approve it.
  • Every action is recorded, so you can see what was done and by whom.

Questions

What teams ask first.

Can you add AI to an application we already have?

Yes. We start with the tasks where AI fits naturally and change only what those tasks need.

Which models do you use?

Whichever fits the task and your obligations: hosted providers, open-weight models on your servers, or a mix.

Who owns the code?

You do. We hand over code, infrastructure, and runbooks your team can run.

Start a conversation

Tell us about the application you want to build.

An engineer replies within 24 hours with how we would approach it.