Custom AI software built for your actual process
We build custom AI software for the processes no product fits, because they are specific to how your business works. That starts with watching people do the job rather than reading the documentation, which is where most of these projects go wrong.
No sales script. You talk to the engineers who'd build it.
Our team works a shifted day so you get real-time standups and same-day turnarounds in your time zone, not next-morning replies.
Every line of code, model weight, and prompt is yours from day one. NDAs and clean IP assignment are standard, not an upsell.
You work directly with the engineers building your system. No account managers sitting between you and the people writing code.
We move from scoping to a working system in production in weeks. Most engagements ship something usable inside the first month.
What we build
Concrete systems we ship, tuned to your data and your stack.
Process discovery first
Every process has a documented version and a performed version, and they differ. We find the performed one before writing anything.
Full-stack AI applications
The AI and the product around it: interfaces, auth, permissions, background jobs, and the boring parts that make it usable.
Integration with legacy systems
Mainframes, vendor portals, and systems with no usable API. There is always one, and deciding how to handle it in week one beats discovering it in week eight.
Handover you can maintain
Your stack, your conventions, documentation and runbooks, and a team that can keep it running without us.
How we work
Scope & evals
We pin down what success means and build the evaluation set before writing the feature, so quality is measured, not guessed.
Build in the open
Weekly demos against real data. You see progress every week and can change direction before it gets expensive.
Ship & instrument
We deploy with logging, cost tracking, and guardrails in place, then tune against production traffic.
Hand off or stay
Take the keys with full docs, or keep us on for iteration. Either way you're never locked in.
Questions, answered
Should we buy a product instead?
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If a product covers 80% of your process, buy it. Custom pays off when the process is how you compete, or when every product covers a different 60% and you would be building the gaps anyway.
What does custom AI software cost?
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It depends on the integration surface far more than on the AI. We scope against volume, time per case, and error cost first, so the conversation is about return rather than day rates.
How do you handle our messy data?
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Build around it and let the escalation log tell you which data problems cost the most. Attaching a data cleanup project to an AI build means both inherit the slower schedule and both tend to fail.
Who owns the code?
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You do, entirely, from day one. Clean assignment and NDAs are standard, which matters if investors will ever run diligence on your stack.
Let's scope your build.
Tell us what you're trying to ship. We'll tell you honestly whether AI is the right tool and what it would take.