Let customers split one invoice across several payment dates.
Anyone can build something that looks good. It’s not enough.
The platform for people building real products, not just prototypes
What’s on your roadmap?
Pull our five weekly reports into one live screen.
Add a members area with tiered plans and saved preferences.
Sync new deals from our CRM straight into the accounting system.
Looks finished. Is it?
Speed is your edge, and we know AI moves quickly. But customers don’t pay for a demo or something that just looks good. They pay for something that works, is tested, versioned, secure.
Loop32 gives your product team AI tooling that works across your whole stack, with production standards built in.
Startup speed; no compromises
The demo is just part of the job. Loop32 was built to do it all.
Why would our platform work for you?
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Work on complex product features, not just front-ends
AI can already write real code; with our tooling, you don’t need to be an engineer to drive it.
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Sandboxed environments with controlled external access
IT sets the rules and the agent never sees your secret tokens.
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Works with your agents and in your infrastructure
You can use our agents or bring your own via MCP. Anything you build lives in your network, so it can access anything you give it access to.
The working loop
Building product is a process of iteration. The faster that iteration, the better you build. Our goal is to improve your loop by improving your agents’ loops.
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The product manager’s loop
Product managers work directly with AI agents in our platform. They tell the agent what they want to build; the agent builds it and shows it to them; they evaluate it, and repeat. This is new, but it’s not novel.
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The agent’s development loop
This is where Loop32 adds its value. Our platform reinvents ‘debugger on a laptop’ for AI agents first. Locality doesn’t matter any more, but speed and visibility still do. Our platform lets agents spin up ephemeral environments of your full software stack, and work in the whole stack simultaneously. They can see all the traffic flowing, point a browser at it, do everything an engineer would do locally. We optimise heavily for iteration speed so agents are never held up waiting for things.
LLMs are very good at implementing business logic into code. But there’s a whole class of problems that engineers solve daily and AI agents ignore unless told otherwise: versioning and release strategies; CI/CD; developer enablement; encryption; authentication; performance. We build answers to those problems into the core of the platform so that many of them don’t need attention at all. Those that do need attention we make as easy as we can, and we bring them to the attention of the agent so they’re handled. This is how product managers can build robust, production software using AI.
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The engineer’s loop
If you’re lucky enough to have engineers supporting your product, we support them to do what they do best without distraction: architect. Engineers convert the feature a product manager wants into the plan that the product actually needs. In this area particularly, LLMs still fall way short. So with our platform, agents bring the problems that require long-term thinking to the attention of engineers, facilitate discussion, and ultimately record and implement the plan.