# SchemaLabs

> Schema is a Data Language Model: the foundation model for tabular data. Raw tables in; understanding, relationships, missing values, and predictions out. Key-less cross-table mapping, vertical-agnostic sector identification, and label-free missing-value imputation, with no shared keys, no labels, and no preprocessing.

## Product
- [Schema-2 model card](https://www.schemalabs.ai/model-card/schema-2): the latest Schema Model, released August 2026, available August 13, 2026: intended use, training data, evaluation across ten benchmark families, and known limitations
- [Schema-1 model card](https://www.schemalabs.ai/model-card/schema-1): retired as of August 13, 2026, and superseded by Schema-2; the card remains published as the historical record of its intended use, training, evaluation, and limitations
- [Model Card registry](https://www.schemalabs.ai/model-card): every documented Schema Model, latest first
- [Platform](https://www.schemalabs.ai/platform): connect raw enterprise data, create model endpoints, and deploy vertical and agentic AI
- [Pricing](https://www.schemalabs.ai/pricing): usage-based cell rates (fresh, cache, batch, synthetic, storage), subscription tiers, and FAQ

## Research
- [Schema-1 paper](https://www.schemalabs.ai/research): the Data Language Models paper, with abstract and benchmarks
- [arXiv preprint](https://arxiv.org/abs/2605.06290): canonical version of the paper

## Solutions
- [Solutions](https://www.schemalabs.ai/solutions): what teams use Schema for, in six groups: understand raw tables, build agents and vertical AI on data understanding, unify systems with no shared keys, no labels, no preprocessing, predict with held-out reports, identify any dataset's industry, fill missing values. Each with real sample output and worked industry examples (finance, healthcare, manufacturing, retail, energy, vertical SaaS)

## News
- [News](https://www.schemalabs.ai/company/news): announcements from SchemaLabs, newest first
- [Introducing Schema-2](https://www.schemalabs.ai/company/news/introducing-schema-2): the Schema-2 release post (August 7, 2026): what the model does in one pass, why vertical and agentic AI need it, and benchmark summaries with links to the full model card

## Company
- [About](https://www.schemalabs.ai/company/about): the SchemaLabs manifesto
- [Contact](https://www.schemalabs.ai/company/contact): email channels and location

## Legal and trust
- [Trust Center](https://www.schemalabs.ai/trust): security and compliance posture overview with links to underlying policies
- [Legal](https://www.schemalabs.ai/legal): index of every customer agreement, privacy policy, and operational disclosure
- [Privacy Policy](https://www.schemalabs.ai/privacy): how SchemaLabs collects, uses, and protects personal information
- [Your Privacy Choices](https://www.schemalabs.ai/privacy-choices): CCPA and CPRA rights for California residents
- [Terms of Service](https://www.schemalabs.ai/terms): agreement governing access to and use of the Service
- [Schema Model License](https://www.schemalabs.ai/model-license): license for the Schema Models
- [Use Policy](https://www.schemalabs.ai/use-policy): prohibited uses, prohibited data categories, and enforcement
- [Cookie Policy](https://www.schemalabs.ai/cookies): cookies and similar technologies
- [Data Processing Agreement](https://www.schemalabs.ai/dpa): processor obligations and Customer Data handling
- [DPA Annex III: SCCs](https://www.schemalabs.ai/dpa-sccs): EU Standard Contractual Clauses for international transfers
- [Sub-Processors](https://www.schemalabs.ai/sub-processors): live list of third parties processing Customer Data
- [Supported Regions](https://www.schemalabs.ai/supported-regions): where the Service is offered and where access is restricted
- [Security](https://www.schemalabs.ai/security): architectural isolation, security controls, incident response
- [Responsible Disclosure](https://www.schemalabs.ai/responsible-disclosure): how to report a security vulnerability
- [Model Card](https://www.schemalabs.ai/model-card): intended use, training, evaluation, and limitations for each Schema Model