Most teams can build AI now. Almost no one can prove it works.
Science4Data builds the computational engines behind specialty businesses: estimating, scoring, underwriting, records. Every one ships with golden-test evidence that it is right, and every one is delivered as a standalone application you own, down to the Docker images and source code. A verified result against your real numbers, with no platform dependency attached.
Both arcs look identical for the first month. Then the edge cases arrive — and the two lines never meet again.
Prototypes are easier to build. Proof takes more.
AI tools have made building applications fast and cheap. Many teams can stand up a semi-working prototype in a week. What the tools did not change is the part that was always hard: knowing whether the answer is right. And your prototyping effort isn't a throwaway either: we build secure, compliant applications from inception, not disposable demos you'll end up rebuilding from scratch.
A bid that's off by 4% loses the job or loses the margin. A score that drifts after a model update fails silently for months. The difference between a plausible AI application and a correct one is invisible in a demo. It only shows up against ground truth. That's the part we industrialized.
Built to go deep, not to run out of steam
Most AI applications follow the same arc: a thrilling first week, a promising first month, then a long stall. The prototype gets to 80% fast because the easy 80% is what AI tools are good at. Then the domain edge cases arrive: the workbook quirk, the carrier's odd file format, the rule that only the senior estimator remembers. Without a foundation built for depth, every fix breaks two other things. The project quietly dies of maintenance.
Our SPL method is designed for the opposite arc. We're not building a prototype to throw away: it's built right from the beginning, with security and compliance in place from day one, not bolted on later. The golden dataset is the foundation, not the afterthought: every domain rule we capture becomes a permanent test, so the engine can only move forward. Depth compounds: each engagement adds edge cases, each model update is regression-proven, and the application gets more correct over time, not more fragile. That is the difference between a prototype that plateaus and an asset that appreciates.
What we sell
Three offers. Each one is built around evidence you can check, not claims you have to trust.
Managed Domain Engines
The computational core of your specialty business: estimating, quoting, scoring, records. Built to reproduce your ground truth, operated by us or handed over entirely, and re-verified on every model and data change. Your domain expertise, made executable and kept correct.
AI Application Assurance
Already building in-house? Good. We'll prove whether it works. We construct the golden dataset and evaluation harness for your internal AI applications, certify accuracy against ground truth, and monitor for drift. Independent verification your own team structurally cannot give itself.
Work With Us First
We'll work with your team for three weeks on a real problem, for a minimal fee. If it's a fit, we keep going. If it's not, we walk away as friends: no long contract, no pressure to continue.
Built for specialty businesses
We serve organizations whose edge is deep domain knowledge: too specific for generic AI, too consequential to get wrong.
Specialty Contractors & Estimators
Your estimating knowledge lives in spreadsheets and senior people. We make it an engine that bids exactly like your best estimator, and prove it against past bids.
MGAs, Insurers & Specialty Finance
Bordereaux, underwriting rules, reconciliation: high-volume, zero-tolerance work where a verified pipeline beats a clever demo every time.
Teams Building AI In-House
Keep building. We supply the golden datasets, evaluation harnesses, and independent certification that turn your prototype into something you can stake the business on.
Start fast. Own it outright. No lock-in.
Every engagement starts on Athena, our internal studio for building AI applications quickly, refined across 100+ use cases. But you never take on a platform dependency. Once the application is proven, we extract its blueprint and deliver a standalone system: full source code, Docker images, and an automated build that deploys wherever you run, on your infrastructure or in Google Cloud. If we disappeared tomorrow, your engine keeps running and any competent team can maintain it. That is the point.
- Blueprint extraction: no Athena dependency ships
- Delivered as full source code + Docker images
- Automated builds to multiple endpoints
- Runs on your servers or Google Cloud
Bring us your hardest number.
A past bid, a settled book, a scored file: anything with a known right answer. We'll build against it, test against it, and show you the report. That's the whole pitch.
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