Schema

A Schema is a formal description of data structure — the columns of a database table, the fields of a JSON object, the elements of an XML document, or the structure of a knowledge representation. Schemas define types, constraints, relationships, and validation rules. Common schema languages include JSON Schema, XML Schema (XSD), GraphQL SDL, Avro, Protobuf, and the schemas embedded in relational and document databases. In AI, schemas appear in many critical places: structured outputs from LLMs ("return JSON matching this schema"), function-calling tool definitions, retrieval indexes, training-data formats, and evaluation result structures. OpenAI's structured outputs feature, Anthropic's tool-use schemas, and Google's structured response capabilities all rely on schemas to constrain LLM output. Tools supporting schemas include Pydantic, Zod, Joi, Avro, and many database-specific tools. AI governance, AI compliance, and AI risk management programs document data and output schemas as part of responsible AI evidence supporting reproducibility across enterprise AI systems.

Centralpoint Enforces Output Schemas Across Every Model: Oxcyon's Centralpoint AI Governance Platform applies structured-output schemas consistently across OpenAI, Gemini, Llama, and embedded models. Centralpoint meters consumption, keeps prompts and skills on-prem, and embeds schema-compliant chatbots into your portals via one line of JavaScript.


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