AI in your software
AI inside the product you already have
If you already run a web app, SaaS product or internal system, you do not need a separate AI tool bolted on the side. You need the AI where the work happens. We add it: summaries on the records your team reads, search that understands a question, an assistant that knows your product, insights that say what to do. We build these into our own products, so we are doing it to our own codebases, not just yours.
AI features we shipped into our own products: call transcription and summarisation onto lead records, AI readings on reports, and an in-product conversational assistant.
The engagement
What we deliver
Feature design
Deciding which AI feature is worth it — and which is a demo that nobody will use twice.
Summarisation and extraction
Long records, calls and threads compressed into what a person needs to act.
Search over your own data
Natural-language search grounded in your records and documents.
In-app assistant
An assistant that understands your product and your user's context.
Safe rollout
Shipped behind flags, measured, and reversible — an AI feature that misfires should never take the product down.
How it runs
From first conversation to live agent
- 01
Find the job
We look for one repetitive, text-heavy job with a clear right answer. Not a strategy deck — a job.
- 02
Design the agent
What it decides, what data it can read, which tools it can call, where it must stop and ask a person.
- 03
Build and connect
The agent, grounded in your own data, wired into the systems it needs — CRM, WhatsApp, sheets, accounting.
- 04
Deploy with a human in the loop
It goes live handling a slice of the work, with a person reviewing what it does before the loop widens.
- 05
Operate and improve
We watch traces of real behaviour and tighten it. An agent is a system you run, not a project you finish.
FAQ
Common questions
Can you work with our existing codebase?
Usually yes. We review the codebase first and tell you honestly what shape it is in before proposing anything.
What if the AI feature makes a mistake in front of our users?
We design for it: grounded outputs, visible sources where relevant, easy correction, and a rollback path. Features ship behind flags.
How long does a first AI feature take?
A focused feature is a matter of weeks, not quarters — provided we scope it to one job and resist building a platform first.
Also from our AI practice
Thinking about ai in your software?
Tell us the job. We'll tell you honestly whether an agent should do it, and what it would take to run it properly.