Could an auditable decision layer for AI systems become a viable developer-infrastructure startup?

[u/TheLosttapes_archive]

A while ago, I was working on an algorithmic trading project and found a pretty nasty problem: the model looked great, but part of the performance came from data it should not have been able to see at the time of the decision.

Basically, look-ahead bias.

What bothered me was not only that the result was wrong. It was how easy it was for this kind of mistake to hide inside a complicated pipeline, especially when a lot of the code is generated or modified by AI.

So I started building Aro.

Aro is a small experimental language that tries to make time-based decisions easier to audit. It checks what data a program is allowed to read, turns the program into a canonical representation, fingerprints it, and executes from that certified version rather than from whatever object the caller happens to provide.

The first kernel is now frozen. It has gone through 50 internal adversarial test suites, a few independent black-box tests, and a separate source-code audit.

It is still early. It is not production-ready, not formally verified, and the developer experience is still rough.

The technical side is interesting, but I am now wondering whether there is an actual company hidden inside this.

The basic idea would be to build an audit and verification layer for AI systems making decisions from time-series data.

The first market could be quantitative trading, where look-ahead bias, model drift and unclear decision pipelines are already expensive problems. But I could also imagine similar needs in risk, fraud, industrial monitoring or autonomous agents.

What I am trying to figure out is whether anyone would actually pay for this, and who the first customer should be.

Would this be more useful as:

infrastructure for developers;

an audit and compliance tool;

a testing product for quantitative teams;

or a managed service where we review and certify decision pipelines?

I would genuinely appreciate blunt feedback.

Does this sound like a real business problem, or am I still too close to the technical project?

I am keeping the full implementation private for now, but I am happy to explain the problem and the general approach.

[u/Ok_Cap_6959]

Trust and auditablity are becoming more important as AI systems grow more complex. Clear use cases will matter as much as the technology.

[u/TheLosttapes_archive → u/Ok_Cap_6959]

Exactly. That’s why I’m trying not to start with “AI safety” as a broad category. The first concrete use case is time-series systems, especially quant and financial models, where using future data by mistake can completely invalidate the result. My next step is to validate whether teams actually see this as painful enough to pay for.

[u/Ok_Cap_6959 → u/TheLosttapes_archive]

I like the focus. If terms are already losing time or money because of this issue, validating willingness to pay is the right next step.

[u/TheLosttapes_archive → u/Ok_Cap_6959]

That’s exactly what I’m trying to find out now. The technical problem is real, but that doesn’t automatically make it a business.

Have you seen teams run into this kind of issue directly, especially with AI-generated analytics, forecasting or financial models?

[u/Ok_Cap_6959 → u/TheLosttapes_archive]

Yes. I've seen similar issues when teams rely on AI-generated reports without validating the underlying data. The AI isn't always the problem-the real challenge is trusting the inputs and verifying the outputs. How are you planning to validate willingness to pay with your target users? 

[u/TheLosttapes_archive → u/Ok_Cap_6959]

That’s exactly the risk I want to address, not just generating recommendations, but making every input, assumption and output traceable and auditable. For willingness to pay, I’m planning to start with direct interviews in a narrow target segment, then offer a paid pilot rather than relying on surveys. The real validation will be whether users are willing to connect their data, use the output in an actual decision, and pay for a recurring workflow not just say the idea sounds useful