
Current AI models have democratised access to general intelligence. It's powerful, accessible and getting better every day.
But the deepest problems in most industries aren't solved by these general foundational models. Humanity's most critical industrial knowledge isn't on the internet. It lives in proprietary processes, sparse datasets, and the minds of experts who've spent decades mastering their domains.
Solving complex, high-ROI industrial problems requires domain-aware AI.
Models that reason through edge cases. Systems with traceability where every decision can be audited. Intelligence built on unstructured, sparse proprietary data that captures tribal knowledge.
We're Second Order Systems, and we build specific intelligence for specific domains.
We co-create AI solutions with industry domain experts.
We partner with domain experts and companies who've spent decades mastering their industries. Together, we identify high-stakes problems and build custom AI that works where general models fail.
If you've spent decades mastering your industry, if you see critical problems that need AI but know general models won't cut it—we partner with you. We work on your proprietary data. We build custom models that capture what you know.
Our approach:
This is an AI Venture Lab. We work across manufacturing, aerospace, energy, retail—anywhere deep domain problems meet scarce data and high stakes.
I'm Udit Agarwal. I've built AI systems for a decade. At Morgan Stanley, I built core AML systems—high-stakes sparse-data problems where traceability and precision aren't optional. Before that, founded Vizal AI building intelligent sales agents.
If you're a domain expert who knows the critical problems in your industry that general AI won't solve—let's talk.
If you're an AI researcher who wants to work on hard problems with real constraints—join us.
Competitive advantage won't come from the best API. It comes from the deepest domain intelligence.