PolyPhaze Knowledge Fabric - 2026 Pricing, Features, Reviews & Alternatives

PolyPhaze Knowledge Fabric is a cloud and on-premises data intelligence platform that connects, resolves, governs, and traces enterprise data across existing systems without requiring data migration or infrastructure replacement. Deployed as an intelligence layer on top of current operational stacks, it ingests from operational systems, document stores, data warehouses, and licensed external sources, then resolves entities into single canonical records with confidence-rated matches. A continuously computed, attribute-level Trust Score travels with every data point, making outputs from both human analysts and AI agents defensible and audit-ready. Deployment targets 30 to 90 days, with self-hosted and air-gapped configurations available for regulated environments.

PolyPhaze Knowledge Fabric serves mid-market and enterprise organizations across Insurance, Energy and Oil and Gas, Manufacturing, Retail and CPG, Federal and DoD, and Mergers and Acquisitions. Role-specific workbenches surface a single canonical truth for executive personas including CEO, CFO, CRO, and COO. A typed relationship graph holds the meaning of relationships between entities, not merely identifier proximity, while zero-trust governance controls, logs, and audits access at the data layer rather than the application layer. AI agent governance ties every agent action to the decisions it produces, with full output traceability and source lineage back to the originating record.

Additional capability sets extend the platform's value across specific use cases. The Data Commerce module identifies internal data with external commercial value, applies compliance classifications, and packages records as sellable data products with quality, lineage, and Trust Score attached. The Asset Twin module unifies OT and IT signals into one trusted record per physical asset for predictive operations. Migration support profiles and validates data correctness before and during ERP cutovers, and M and A support connects data room documents, management interviews, and operating systems from diligence through exit preparation. The platform is model-agnostic, operating with any public or private AI model so that a change in model does not disrupt the governed data foundation.