# CoreModels > One connected core model of what your data means. Warehouses and pipelines, APIs and event streams, ontologies and content models, published standards and the schemas you wrote yourself. A library of connectors, and one governed model your team edits and every agent reads. ## Product - [Home](https://coremodels.io/): One connected core model of what your data means. Warehouses and pipelines, APIs and event streams, ontologies and content models, published standards and the schemas you wrote yourself. A library of connectors, and one governed model your team edits and every agent reads. - [CoreModels Solution Framework](https://coremodels.io/framework): How an organization keeps one connected core model of what its data means — across every system it runs and every agent it points at that data — and what CoreModels does to make that model real, governed, and readable at runtime. - [The Core Model](https://coremodels.io/framework/core-model): A core model is the one place your organization writes down what its data means, so every system and every agent can read it instead of guessing. - [Coherence: meaning survives many handoffs](https://coremodels.io/framework/coherence): A request inherits terms the estate holds. Those terms are mapped to meaning across many uses. When the meaning survives every mapping, that is coherence — and it is a capability, not a value statement. - [Why CoreModels](https://coremodels.io/framework/why): Your systems already know what your data is. None of them knows what it means across the others. CoreModels holds each model as it is and keeps the mappings between them alive. - [From ingestion to execution in five steps](https://coremodels.io/framework/how-it-works): Connect and ingest, model and map, collaborate and govern, expose and execute, adapt and scale — the mechanism behind the three steps on the landing page. - [What a Core Model can do once it exists](https://coremodels.io/framework/capabilities): Graph-based modeling, adjustable meta-models, collaboration and suggestions, import-map-compare, precision editing, validation and governance, transformation across formats, and the agent endpoint. - [Who it serves](https://coremodels.io/framework/who): Six kinds of team keep meaning somewhere. One model lets them keep it together — data and pipeline, standards and ontology, API and interface, content and semantics, research and domain, business systems and contracts. - [The Schematica Suite](https://coremodels.io/framework/suite): CoreModels is the engine. The Suite is what it powers: the Schematica Library, the MCP server, the design plugins — and the wider ecosystem of standards they connect to. - [Q&A](https://coremodels.io/q-a): Frequently asked questions about CoreModels, schema modeling, and semantic data platforms. - [Connectors](https://coremodels.io/connectors): Bring the file your tools already produce. No passwords. Every card says what you can do today. - [Pricing](https://coremodels.io/pricing): Builder $49/mo. Team $990/mo with 10 seats. Founding teams $5,880 for year one, billed annually, through 30 September. 14-day free trial. - [Guides](https://coremodels.io/guides): Articles that explain the gap, then point at the recipe that closes it. ## Documentation - [CoreModels Docs](https://learn.coremodels.io): Guides, tutorials, and core concepts for modeling with CoreModels. - [API Reference](https://learn.coremodels.io/user-guides/integration-apis/reference): Integration APIs for connecting CoreModels to external systems. - [MCP Server](https://library.schematica.io/mcp-server): Model Context Protocol server for AI tooling integrations. ## Optional - [Get started](https://go.coremodels.io/app): Sign in and open CoreModels. - [About ARAMAI](https://www.aramai.net/company#about-tab): Company background, contact information, and careers. - [Privacy Policy](https://www.aramai.net/privacy-policy): Privacy practices for ARAMAI and CoreModels services. ## CoreModels Solution Framework - [CoreModels Solution Framework](https://coremodels.io/framework): How an organization keeps one connected core model of what its data means — across every system it runs and every agent it points at that data — and what CoreModels does to make that model real, governed, and readable at runtime. - [The Core Model](https://coremodels.io/framework/core-model): A core model is the one place your organization writes down what its data means, so every system and every agent can read it instead of guessing. - [Coherence: meaning survives many handoffs](https://coremodels.io/framework/coherence): A request inherits terms the estate holds. Those terms are mapped to meaning across many uses. When the meaning survives every mapping, that is coherence — and it is a capability, not a value statement. - [Why CoreModels](https://coremodels.io/framework/why): Your systems already know what your data is. None of them knows what it means across the others. CoreModels holds each model as it is and keeps the mappings between them alive. - [From ingestion to execution in five steps](https://coremodels.io/framework/how-it-works): Connect and ingest, model and map, collaborate and govern, expose and execute, adapt and scale — the mechanism behind the three steps on the landing page. - [What a Core Model can do once it exists](https://coremodels.io/framework/capabilities): Graph-based modeling, adjustable meta-models, collaboration and suggestions, import-map-compare, precision editing, validation and governance, transformation across formats, and the agent endpoint. - [Who it serves](https://coremodels.io/framework/who): Six kinds of team keep meaning somewhere. One model lets them keep it together — data and pipeline, standards and ontology, API and interface, content and semantics, research and domain, business systems and contracts. - [The Schematica Suite](https://coremodels.io/framework/suite): CoreModels is the engine. The Suite is what it powers: the Schematica Library, the MCP server, the design plugins — and the wider ecosystem of standards they connect to. ## Connectors - [All connectors](https://coremodels.io/connectors): Vendor and standard connectors with recipes and use articles. - [Airbyte](https://coremodels.io/connector/airbyte): Govern the catalog every sync trusts - before a silent type change lands in the warehouse. - [Apache Airflow](https://coremodels.io/connector/airflow): Govern the scheduler that already knows your freshness, ownership, and lineage. - [Apache Avro](https://coremodels.io/connector/avro): One governed reading of the schema that currently lives in four places. - [Google BigQuery](https://coremodels.io/connector/bigquery): Turn INFORMATION_SCHEMA from an inventory into a contract you can audit. - [cBioPortal](https://coremodels.io/connector/cbioportal): Govern the four comment rows that are the schema of your study. - [Confluent](https://coremodels.io/connector/confluent): Put meaning under every Kafka subject the Schema Registry already inventories. - [Schema Converter](https://coremodels.io/connector/converter): A neutral hub between fourteen schema formats, with an honest lossiness ledger. - [Databricks](https://coremodels.io/connector/databricks): Give Unity Catalog something to check thousands of columns against. - [dbt](https://coremodels.io/connector/dbt): Meaning has no home in dbt. Bring a manifest; we turn `accepted_values` into a vocabulary you can govern and your agent can read. - [Microsoft Fabric](https://coremodels.io/connector/fabric): Catch the warehouse type change that never pages anyone. - [General](https://coremodels.io/connector/general): Every system in your estate holds a fragment of meaning. None of them holds the whole. - [AWS Glue](https://coremodels.io/connector/glue): Stop treating a crawler snapshot as the meaning of your lake. - [JSON-LD](https://coremodels.io/connector/jsonld): Make the vocabulary you already trust executable downstream. - [JSON Schema](https://coremodels.io/connector/jsonschema): Stop asking a validator four questions it was only built to answer one of. - [LinkML](https://coremodels.io/connector/linkml): Let the pipeline read the model that is already right. - [Neo4j](https://coremodels.io/connector/neo4j): Write down the graph schema MERGE has been inferring for you. - [ODCS](https://coremodels.io/connector/odcs): Make the contract a derived artifact of governed meaning, not a YAML twin of the table. - [MACH ODM](https://coremodels.io/connector/odm): Stop shipping a recollection of the standard as if it were the standard. - [Open Semantic Interchange](https://coremodels.io/connector/osi): Put two revenue numbers next to the same definition. - [OWL](https://coremodels.io/connector/owl): Keep the ontology and the application schema from becoming two portraits of Person. - [Protocol Buffers](https://coremodels.io/connector/protobuf): Carry reserved field numbers with the meaning, not only with the .proto file. - [REDCap](https://coremodels.io/connector/redcap): Diff the codebook so a study change is a review, not a memory. - [Salesforce](https://coremodels.io/connector/salesforce): Govern the org whose schema can change in forty seconds from Setup. - [ShEx](https://coremodels.io/connector/shex): Keep the four assertions in every shape constraint from dying in a hand copy. - [Snowflake](https://coremodels.io/connector/snowflake): Your Snowflake schema is not a contract. Generate one from the governed model. - [SQL](https://coremodels.io/connector/sql): Give the column nobody can explain a rule the database can actually carry. - [Azure Synapse](https://coremodels.io/connector/synapse): Record the constraints that die on the way to a registered schema.