Industries
Developer platforms and internal tooling — the software your engineers stand on.
Typical timeline 8–16 weeks to first production release
What actually breaks here
Tools for engineers fail differently: your users can read the stack trace. Generated code nobody wants to maintain, internal platforms that drift from the workflows they were built for, and AI tooling that demos well but cannot be trusted with tenant boundaries. Developer tools earn adoption or they die — nobody can force an engineer to like a platform.
What we build
Code generation that emits software a human wants to own. Internal platforms and agent systems with organisation-scoped retrieval, because a filter you forget is a data leak. Developer-facing APIs with contracts, versioning and error messages written for the person debugging at 2am.
When an existing product beats a build in Dev Tech
We would rather tell you this now than three months in.
| Dimension | Building it | When Dev Tech SaaS works |
|---|---|---|
| Fit to your process | Built around how you actually work, including the parts that are unusual. | Fits if your process is close to the industry norm — and many are. |
| Time to first value | Weeks. Nothing works until the first release. | Days. This is the real advantage, and it is a big one. |
| Ongoing cost | You own the code and pay to maintain it. | Per-seat forever, but somebody else carries the maintenance. |
| Integrations | Whatever you need, including the internal system nobody else has. | Whatever the vendor supports. Check before you commit. |
| When it breaks | You decide the priority, because it is your team. | You file a ticket and wait with everyone else. |
| Leaving | The code and the data are yours. | Export what the vendor lets you export. |
Common questions
What have you actually built in this space?
Two of our three products are developer tooling: a builder that turns a structured brief into a working, idiomatic Django application, and an AI-native agency operating system with twenty-five specialist agents working over organisation-scoped retrieval. Both are publicly reachable — click through and judge the engineering yourself.
Do you build AI agent systems?
Yes, and the hard part is never the model — it is retrieval scope, evaluation, and cost control. We build those first, because an agent you cannot evaluate is an agent you cannot ship.
$ tell us what you're building and where it's stuck
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