The Unified Schema Source of Truth for Humans and AI
CoreModels makes data structure and meaning transparent, governable, and reusable. across teams, systems, and AI workflows. It brings together business logic, transformation rules, and schema definitions in one place, creating a shared foundation for integration, automation, and intelligent reasoning.
See how CoreModels simplifies schema management, transformation control, and AI-driven automation.
Try it for freeWhy CoreModels?
Bridging the gap between humans, systems, and AI
Creating Alignment Across Humans, Systems, and AI
When schemas and transformation logic are hidden in code, subject matter experts rely on developers for every update, and AI systems lose context. CoreModels exposes and connects these definitions, establishing a shared foundation where humans and machines interpret data consistently. This alignment minimizes friction, eliminates redundancy, and reduces rework across complex ecosystems.
Built for Modern Data Pipelines
At the heart of ETL and ELT workflows, CoreModels functions as a structural and semantic control layer that governs the transformation process across data systems. It manages how data is reshaped, validated, and mapped, ensuring every transformation maintains consistency with both technical definitions and business meaning. By centralizing transformation logic, mappings, and schema relationships, CoreModels enables pipelines to adapt dynamically as models evolve.
Designed for Flexibility
In a world where data structures, APIs, and AI workflows evolve faster than traditional tools can keep up, CoreModels provides the flexibility to adapt. It is a graph-based low-code modeling platform built on adjustable meta-model templates that support a wide range of data representation formats. Whether managing JSON Schemas, JSON-LD definitions, or configurations that drive transformations and orchestration, CoreModels adjusts seamlessly to organizational and technical needs.
Unified Environment for Data Ecosystems
CoreModels enables teams to model, extend, and connect structural and semantic definitions within a unified environment—ensuring resilience as data ecosystems continue to change. This unified approach minimizes duplication, prevents schema drift, and ensures reliable, governed data flow across distributed and hybrid architectures.
Unified Source of Truth
Centralised Models and Mappings
Single Schema Graph
All structural and semantic definitions live in one connected graph, accessible via intuitive UI and APIs. No more hunting through scripts, notebooks or integration code.
Typed Mappings
Define how model entities relate across systems. Preserve business meaning, enforce constraints and ensure interoperability.
Real‑Time Availability
AI agents, services and developers query authoritative schemas at runtime rather than relying on hard‑coded assumptions.
Collaboration Without Bottlenecks
SME Empowerment
Business experts can add, modify and manage definitions and rules directly. No developer intervention required.
Real‑Time Collaboration
Collaborative editing with suggestions and comments keeps everyone aligned.
Audit & Versioning
Track changes, generate reports and maintain a full history of your models.
Graph‑Based Low‑Code Modeling Platform
Adjustable Meta‑Models
CoreModels comes with a set of default meta‑model templates for common formats, but everything is customizable. You can extend existing templates or build your own, supporting:
- JSON Schema for API and service definitions.
- JSON‑LD and linked‑data models for rich semantics.
- Configurations that drive transformations and orchestration (including YAML-based workflows and mappings).
- Custom formats designed to align with your organization’s unique data structures and integration logic.
Effortless collaboration and suggestion
collaborate with your team on data models in real time. This makes it easy to get feedback and make changes, ensuring that everyone is on the same page.
Import, Map & Compare
- Seamless Ingestion: Bring in models from existing systems or upload new definitions via simple import flows.
- Mapping & Comparison: Align disparate schemas, highlight differences and reconcile mismatches quickly.
- Expandable Export: Share your refined models in the formats you need—whether for documentation, code generation or integration with other tools.
Precision editing and customization
CoreModels gives you the power to fine-tune your data models to meet your specific needs. You can specify required attributes, create custom relationships, and more.
Validation & Governance
- Rule Definition: Specify required attributes, custom relationships and constraints.
- Automated Validation: Catch errors before they propagate, and guarantee schema integrity across pipelines.
- Audit Trails: Maintain a transparent record of who changed what and when, ensuring compliance and trust.
Scalable & Efficient
Built as a cloud‑native service, CoreModels scales to handle large data sets and complex model libraries. It integrates smoothly into your existing stack and keeps performance high as your usage grows.
Empowering the Schematica Ecosystem
The Schematica Library is a community‑driven catalog of production‑ready data models, ontologies, taxonomies and content structures. CoreModels is the operational engine behind this library:
Discover
Browse curated knowledge models across healthcare, legal, e‑commerce, web standards, enterprise and more.
Activate
Import these models into CoreModels, adapt them to your needs, and extend them with your own definitions.
Operationalize
Expose them via API and MCP interfaces so AI agents and integration services can query authoritative schemas in real time.
Together, Schematica and CoreModels turn knowledge discovery into knowledge execution—accelerating integration, ensuring compliance and powering smarter AI.
Benefits by Role
See how CoreModels empowers different teams across your organization
Data Engineers & Developers
Accelerate ETL/ELT transformations with a semantic control layer; map and align schemas without rewriting code; reduce redundancy and schema drift.
AI/ML Engineers
Improve model accuracy and reasoning by referencing structured, authoritative schemas; enable agentic systems to query real‑time schemas via MCP; reduce hallucinations and training overhead.
Enterprise Architects
Gain a governed view of relationships and dependencies across the enterprise; leverage industry‑standard models (e.g., FHIR, Schema.org) with confidence; build future‑ready architectures.
Subject Matter Experts
Define and manage business rules directly; collaborate without waiting for developers; track changes and maintain regulatory compliance.
Industry Specialists (Healthcare, Legal, E‑commerce)
Access domain‑specific models built with best practices; ensure regulatory compliance; accelerate deployment and integration.
Use Cases & Impact
Real-world applications transforming how teams work with data
Healthcare Data Modeling
In healthcare, data silos and complex interoperability standards slow down progress. CoreModels transforms these challenges by streamlining mapping between FHIR resources, device schemas and clinical data structures. Teams can co‑develop and refine models, implement transformations quickly and ensure compliance. This allows healthcare organisations to redirect efforts toward patient care and research instead of plumbing.
Cross‑Domain Integrations
Whether connecting CRM and ERP systems, harmonising product catalogs in e‑commerce or bridging legal document repositories with case management, CoreModels provides typed mappings and semantic validation that accelerate integration projects and reduce errors.
AI‑Ready Knowledge Infrastructure
AI agents perform better when they understand the shape and meaning of data. By exposing a machine‑readable schema network, CoreModels enables agents to validate inputs, generate transformations and adapt to changes autonomously, boosting reliability and speeding up deployment of generative AI solutions.
Rapid Schema Evolution
Business rules and data structures change constantly. CoreModels reduces schema change cycles from weeks to hours, with up to 90% of changes made directly by SMEs. AI validation success rates soar from 30% to over 98%, and redundant integrations fall by 70%, saving millions in engineering and operations costs.
How It Works
Transform your data architecture in five simple steps—from ingestion to execution
Connect and Ingest
Import schemas from source systems, databases, APIs, YAML configs or the Schematica Library. Auto‑discovery tools pull in structural and semantic definitions from existing systems.
Model and Map
Use visual editors and low‑code tools to define entities, relationships and constraints. Create typed mappings across systems and formats, and compare versions to ensure consistency.
Collaborate and Govern
Invite SMEs, developers and AI agents to co‑edit models. Apply validation rules, track lineage and maintain a governed record of changes.
Expose and Execute
Deliver your models via API and MCP interfaces to data pipelines, integration platforms and AI services. Use CoreModels as the semantic control layer for your ETL/ELT workflows.
Adapt and Scale
Extend your meta‑model templates, evolve with industry standards and handle new data formats effortlessly. CoreModels grows with you as your data and AI ecosystem expands.
Ready to Build the Foundation of Structured Intelligence?
CoreModels forms the intelligence layer connecting humans, systems, and AI through a unified schema framework. It enables organizations to define, evolve, and operationalize knowledge across pipelines, applications, and intelligent agents.
By transforming buried structures into living, machine-readable assets, CoreModels turns static definitions into dynamic, executable intelligence.
As part of the Schematica ecosystem, CoreModels bridges knowledge discovery and execution, ensuring that every system, model, and agent operates from a shared understanding of data and meaning. It is the foundation for structured intelligence—governing how transformation, semantics, and interoperability work together across the modern enterprise.