We turn your dev team into agentic operators.

Diagnostic, setup, team autonomy.

How we work: forward-deployed

An engineer joins your team, sets it up, and leaves you running it.

We work inside your codebase, with your people. That is what forward-deployed means here. A good engagement leaves you independent of us. Most consulting is priced the other way round.

1. 1

   Embed

   One of our engineers joins your team: your repos, your stack, your review culture. Half senior engineer, half consultant. We scope the real problem with your developers and your CTO before anything gets built.

2. 2

   Deploy

   We install Niwa and the agentic operating model on your repositories and standards. Tickets with criteria, agents on their own branches, a separate reviewer, and a gate before anything merges. Your controls stay where they are.

3. 3

   Hand over

   Your developers run it day to day and your leads can coach the next person. Then we leave. If you still need us in six months to keep the agents running, we did it wrong.

What makes this different.

• Augment, never replace

  Your devs become the operators. A good dev running good agents beats either alone.

• Respect the environment

  We transition the team you have, on the stack you have. No rip-and-replace, no greenfield fantasy.

• We're developers

  We've shipped AI to production and felt every failure mode. We understand devs because we are devs.

We run this on our own fleet.

We've done this on real teams. We trained Clareo Systems' quant developers to run agents inside a high-stakes finance environment, on their own standards. Their CTO and team now operate agentic workflows in their own repo. We run the same way on our own software: Niwa, Trovex, Yoru, WRAI.TH and Dokan.

Who this is for.

Straight answers.

Isn't AI easy now? We already have the seats.

Seats give your team a copilot, autocomplete and Q&A in the editor. That's real, and it's about 10% of what these models can do. The other 90%, agents running real work reliably in production, is an operating problem (context, orchestration, observability, trained operators), and none of it comes in the license. The "AI is easy" feeling is exactly the gap between a demo and production. If it were easy, your team would already be there.

Isn't the point of AI to ship cheaper?

No, and if cheaper is the goal we're not the right fit. The point is prod-grade output from the team you already trust. We're not here to shrink your team or your budget; we're here to make a good team dramatically more capable. Teams that chase "cheaper" tend to ship more mediocre work faster, which is not the same thing.

Will you replace our developers?

No. Our entire model is the opposite: your developers become the agentic operators. We augment them. A good developer running good agents beats either one alone, and a team that fears being replaced will never push the tools to their limit. We make your devs stronger and far more productive, not redundant.

Why you, and not a freelancer or a big consultancy?

A freelancer can write you some prompts; they rarely run agent fleets in production or transfer a durable capability to your whole team. A big consultancy will sell you a slide-heavy "AI transformation" by people who haven't shipped it. We're a small studio of developers who run this in production on our own products. You get builders who've done the thing, working on your real codebase, leaving your team able to keep going without us.

Why a paid assessment before an engagement?

Because a real plan comes from your actual repo, not a sales call. The assessment is fixed-scope and the plan is yours to keep, whether or not we work together after. It also means we only take on engagements we're sure we can move, so you're not paying us to discover the problem.

Do you respect our existing environment, or do we start over?

We respect it. We transition the team and stack you have, inside your conventions and controls. The whole point is to upgrade how your existing system works, not to replace it with ours.