Open science is powering the Tabular Foundation Models revolution
By Gaël Varoquaux
The tabular AI company
Build reliable Tabular AI models faster.
We build software that helps enterprises make reliable predictions and better decisions based on their tabular data. Not just faster ones.
skore / churn-model / validation
SKORE VALIDATES
- Passed:Model structure is valid
- Passed:No data leakage detected
- Warning:Validation split is missing
- Warning:Metric does not match the question
- Passed:Record generated — run can be repeated
3 passed · 2 warnings · 0 errors
REVIEW NEEDED
Stewarding scikit-learnOver 200 million downloads per month
Driving TabICLThe SOTA fully open source tabular foundation model
Any AI provider.Any ML framework.
Any compute.We work with
Why data science still needs human judgment
Data science is being rewritten by agents faster than the discipline can absorb it.
AI accelerates data science, but it can’t replace human judgment.
For the business, that difference determines what you can explain, forecast, control, and protect.
Models nobody can explain.
The issue is not the time to review. It is the opacity of results generated by AI.
AI bills that can’t be forecast or justified.
Token and compute consumption is unpredictable and hard to attribute, which makes forecasting the cost of a data science workload challenging.
Technology lock-in.
Each AI tool decision narrows the next. The model, framework, and infrastructure are chosen for you, resulting in vendor lock-in you can’t easily get out of.
Know-how walks out in a text file.
Hard-won expertise written into prompts and agentic skills documented as plain-text turn know-how into leakable IP, while agentic access to production data is largely ungoverned.
What Probabl changes
Scale faster, stay compliant, show your work.
Predictive modeling is an empirical discipline. We build the software that enforces statistical methodology across human and AI-agent workflows, preventing errors upstream, recording full model provenance, and fitting seamlessly into your existing stack.
See what Skore can do for your enterprise
AI that makes you a better data scientist
Routine work automated, judgment preserved. Skore catches data leakage and silent methodological errors as it builds models, enabling data scientists to ship reliable models faster.
Lower total cost, faster time to value
Zero adoption cost, nothing to migrate. Licence, tokens, and time all combined in one equation. Use right-sized models, only consume the tokens the task needs, and ensure errors never reach production.
Confidence to deploy, operate, and grow
Governed access to AI agents, and an audit trail that is generated by design rather than assembled as an afterthought. Maintainable with any AI provider, any ML framework, any compute – cloud, on-premise or local.
AI transformation you own
Your teams’ judgment compounds into private skills that stay yours, so data science remains a competitive asset – and your tools adapt to your strategy, not the other way round.
“Building predictive models isn’t just writing code – it’s an empirical discipline. Probabl gives your teams the freedom to leverage AI agents at full speed, with absolute confidence that your statistical methods, lineage, and models are defensible.”
Gaël Varoquaux
Co-Founder & Chief Scientist, Probabl
Discover Skore
Quality built into every step of the agentic data science workflow
Skore is the Tabular AI platform for teams that ship predictive models with confidence. Its agent builds, validates, and tracks models and applies the statistical methodology of the scikit-learn maintainers at every step. Skore helps data scientists build reliable Tabular AI models faster.
Build reliable models faster, with your agent assisting at every step.
You make every decision while Skore suggests next steps, flags methodological pitfalls, and takes on repetitive work, following the best practices of the scikit-learn maintainers.
Tell the agent what you need and manage how it interacts with you.
Define your goal, data, and constraints, then choose how often Skore checks in with you. It builds and validates the model and hands it back to you with evidence of every step it took.
Compare experiments, stay on track.
Every run is tracked automatically, so you can compare models, parameters, and results side by side and see exactly what changed from one run to the next.
Metrics that match the question you are asking.
Skore chooses evaluation metrics that fit your problem and data, and reports uncertainty alongside scores, so you know how far each result can be trusted.
AI agents work inside a bounded, credentialed workspace.
Agents only reach the data, tools, and compute you grant them access to. Credentials are scoped to each workspace, so nothing runs outside the boundaries you set.
Every run leaves a record your auditors can follow.
Skore documents the inputs, decisions, and outputs at every step of the pipeline, providing a complete, traceable history for reviews and audits.
Move fast and bullet-proof your Tabular AI models.
Whether you are scaling AI agents across the enterprise or elevating your data science workflow, Probabl provides the methodology layer to move fast with complete accountability.
Insights
AI Data Scientist Blog
Enterprise decision-making grounded in science.
Written by the creators and stewards of scikit-learn.