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Companies want to combine in-house models with external intelligence, but lack a framework that is both secure and extensible. Running workflows outside their environment raises compliance, data governance, and IP protection concerns.
Consultants want to service companies, but don’t have the means to build out a full scale ML orchestration pipeline and lack specialised models to service customers needs
Core Benefits
- Deploy in your own cloud for maximum control and compliance
- Reuse and standardize data streams via a canonical graph
- Leverage Crunch ecosystem models securely through TEEs
- Seamlessly integrate your in-house models with external models
- Extend with custom modules via open-source, BSL-licensed code
Key Features
- Ontology — Standardizes and reuses input streams within your cloud workflows.
- Privacy Preserving (TEEs & MPC) — Run encrypted third-party models outside or within your cloud infrastructure. We ship with TEEs and MPC to keep the models and data private.
- Model Composition — Ensemble, chain, and integrate Crunch ecosystem models with your own.
- Workflow Management — Define and automate any type of ML workflow, from simple chains to complex orchestration.
- Open Source + BSL — Extend and adapt the engine while maintaining enterprise-grade protections.
