Solutions / Agentic Platform Studio
Build an Agentic Software Factory
We build the factory underneath your AI work: the infrastructure it runs on, the assembly line that produces the changes, and the evidence trail an auditor will ask for. It's open source and it installs into a cluster you already own, so there's no procurement cycle to clear. We build it, run it alongside your team, and hand it over with the runbooks.
Vendorless Solution
Installs open source into infrastructure you own
9x throughput
1 dev, 1 month. Previously 3 devs, 3 months.
Your AI features are outpacing your platform
Two things sit underneath every AI feature: what it runs on, and how the work gets made. When neither was designed for agents, it shows up in three places.
AI delivery is slower than expected
Leadership wants AI leverage, but the team still seems to lag every request. The delivery process was designed for humans writing every line, and the work no longer arrives that way.
AI demos are not becoming products
Good AI ideas stall between prototype and production because procurement, environments, and robustness are not set up for speed. The demo works; the launch slips.
Nobody outside engineering can see the work
Asking for a change means finding the right person, explaining it twice, and waiting for a status update. There is no single place a request goes in and comes back as something you can click, so the people closest to the customer stay furthest from the software.
Every one of these traces to the same thing. The delivery process was designed for humans writing every line: the meetings, the handoffs, the sign-offs, the status updates. The work no longer arrives that way, so a lot of that process is now performed rather than useful. It looks like control and produces very little of it.
The shift
The factory still runs. Nobody redesigned it when the work changed.
Three routes from an ask to production. Only one of them was designed around agents.
Built for humans
Slow, but legible
- Business request
- Intake, shaping, and prioritization
- A year in the backlog
- Release
Bypassed by agents
Fast, but fragile
- Prompt or prototype
- Agent-assisted change
- Review burden
- Production risk
The designed factory
Fast, legible, and governable
- Stakeholder ask
- Shaped with Agents
- Agent builds and tests
- Reviewed as running software
- Merge, with the trail attached
What we install
Six parts of the factory, each described by what it changes rather than what it is called.
Your hardware. Your rules. No purchase order.
The whole platform installs onto infrastructure your company already runs and already approved. Nothing is licensed, and you control what data leaves your walls.
Production Adjacent Local Environments
A new engineer, or a new agent, is productive the same morning instead of losing a week to setup. What they build in matches what production runs, so "it worked on my machine" stops being a category of bug. Fewer surprises late, and estimates that hold up.
Every project begins at month three.
Auth, testing, CI, deployment, and observability are already in place on day one, in whatever stack your team uses. Your first sprint goes into the product instead of the plumbing you were going to build anyway.
The project remembers, even when people leave.
Meetings, decisions, docs, and designs land in one place the agents actually build from, so context stops living in one person's head or a Slack thread nobody can find. The other half faces outward: the plan, the progress, and the recap in a link you can send to a stakeholder instead of writing a status deck.
From "this is broken" to a preview link.
A user's request becomes a ticket, becomes a real change, becomes a preview URL you can click before anything merges. You review working software rather than a status update. It ships as part of the engagement and keeps running after the team rolls off, so the loop is yours.
Speed you can still maintain in two years.
Moving fast is worthless if it leaves behind code nobody dares change. Every project passes a scored architecture review before it proceeds, covering the things that actually rot: structure, test coverage, dependency risk, operational readiness. We ran it against our own platform first, scored an F, and fixed it before selling it to anyone.
We ran the factory on ourselves first
This site was rebuilt with the same agentic delivery loop we install for clients. One developer, one month. The previous migration of rangle.io took three developers three months.
Every part of it runs on our own work before it runs on yours. Our projects start from the same starters, our environments come up the same way, our changes arrive as something you can click, and our own platforms get scored by the same review. That is why it hands over with the operating discipline attached rather than an install guide.
Read: how we rebuilt rangle.io
What you are actually adopting
Not a SaaS contract. Open source, installed into infrastructure you already own, so there is no vendor review, no data processing agreement, and no budget line waiting on next fiscal year.
Runs where you already have approval
Your cluster, your security posture, no boundary to re-certify.
Customizable down to the source
Shaped around how your teams work. Nothing in it is a black box.
Nothing licensed, nothing rented
No seat count, no renewal, no dependency on someone else's uptime.
Yours when we leave
You keep the running system and the source behind it.
Find out what the factory looks like in your cloud
Book a demoTooling that clears a regulated review
Most agentic tooling cannot be used in a regulated environment at all. It is SaaS, it wants your source on someone else's infrastructure, and the review that would approve it outlasts the project it was meant to speed up.
Everything in the factory is open source and runs inside your own boundary, on the cluster and under the security posture your auditors already approved. The model endpoint is a choice you control: your account, your region, or a model you host yourself. Nothing here asks for an exception to a policy you already wrote.
It also produces the evidence while it builds. Every action, human or agent, is logged, permissioned, and rate-limited, so nothing has to be reconstructed from git history against a deadline.
We have shipped in regulated markets for over a decade: medical devices with CE marking, government AI deployments, pharma applications under regulatory oversight. If your AI feature is a quarter away from an audit you cannot slip, that is the conversation worth starting.
Capabilities behind the work
Agentic Product Engineering
Agentic Product Engineering
AI-augmented engineering workflows that ship production systems in weeks, not quarters.
See how we help
Agentic AI
Agentic Solutions
Apply AI to product problems. Agents, workflows, and smart experiences that reset customer expectations.
See how we help
Operating Model
Product & Platform Operating Model
Align teams around a product and platform model that supports real delivery speed.
See how we helpIf your platform problem is shaped a little differently
The studio is the premium end of the range: we build the factory and run it with you. If your starting point is closer to one of these adjacent problems, begin there and we'll pull the studio work in when it lines up.
Want the team running the platform after we leave, not the platform run for you?
Build engineering capabilityFoundation in place, and now you need a sustainable way to keep evolving the product on top of it?
Agentic product evolutionAI feature work where the regulator and the infrastructure aren't the primary constraints?
Ship AI features
Coming off a legacy stack, and modernizing what you have matters more right now than redesigning how you deliver?
Modernize your stackAI outpacing the platform under it?
Bring the problem. Watch it get built.
Point at the part that isn't working, then watch us take it through the factory on a call, from the ask to a preview link you can click. You'll know in one call whether this works on your problem. No deck-ware, no compliance theater.
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