Document knowledge extraction
Runs LLM-powered extraction pipelines that parse complex documents into structured, source-anchored knowledge elements with provenance back to the original text.
Read moreBuilding block
AI Interop Services
AI Interop Services connect large language models, document extraction engines, and retrieval-augmented generation to the ontology-grounded knowledge layer. The service handles prompt orchestration, structured output parsing, and source-anchored provenance so that every AI-generated insight can be traced back to its evidence. It supports multi-model routing, approval-gated agent workflows, and domain-specific fine-tuning hooks.
What this enables
What AI Interop Services supports.
Semantic data integration
Provides multi-model AI routing and structured output parsing that transforms unstructured and semi-structured sources into ontology-aligned data ready for integration.
Read moreAuditable digital thread
Records every AI inference, prompt, and model version in the provenance chain so that AI-generated insights carry full traceability from input to output.
Read moreAI agent orchestration
Orchestrates multi-model agent workflows with approval gates, tool routing, and structured output parsing — letting AI handle the groundwork while humans make the judgement calls.
Read moreApplied domains
Where ai interop services has been used.
Financial services
Ontology-grounded risk, compliance, AML, and data lineage for regulated financial workflows.
Read moreEngineering
AI-assisted design for industrial and process engineering, with document-grounded knowledge, simulation integration, and auditable deliverables across regulated sectors.
Read moreHealthcare
Semantic data integration pipelines for medical device data, patient records, and health analytics built on bCLEARer architecture.
Read moreMedia rights
Knowledge-driven rights management and content provenance tracking across media supply chains.
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