The governed intelligence stack behind the field cases. Ten capabilities across four layers: from AI-ready data pipelines to personified workbenches. This isn't a product pitch — it's context for what makes the architectures in the field cases possible.
See the full AIR story →Three governing layers
The stack isn't a platform in the vendor sense. It's a method: certify the data, encode the knowledge, compose the workflow — in that order, every time.
Data quality certification (10-dimension composite trust score), PII/PHI redaction, and pipeline-native lineage registry. Agents don't touch uncertified data.
Insurance ontology, document intelligence, and versioned knowledge repository. Appetite rules, jurisdiction statutes, and SOPs encoded and traceable — not floating in model weights.
Agentic recipe packs for WC/Auto/Property claims and commercial underwriting. Every tool invocation is traceable to the governing chunk, version, and effective date that produced it.
Data quality certification (structured and unstructured) before AI consumes it. 10-dimension composite trust score.
GA1,100+ sensitive data types detected and redacted in-pipeline before egress. PHI, PII, PCI, HIPAA, GDPR.
GAPipeline-native lineage registry. The trust control plane for AI data consumption across Snowflake and Databricks.
PreviewInsurance ontology + document intelligence + knowledge repository. The context layer for governed AI.
GAAI-powered entity resolution. MDM pre-assessment in days, not weeks. Customer identity that carriers trust.
GAEvery AI decision reconstructible from governing chunks, version, effective date, and trace path.
PreviewInsurance agentic workflows for WC/Auto/Property claims and commercial underwriting. Each tool invocation is traceable.
GAClaims examiner intelligence workspace. Facts, intelligence, and evidence in a single cockpit from FNOL intake.
GA1,425+ curated knowledge chunks. NAICS/SIC crosswalk with 7,700+ reference records. 8,500+ typed ontology edges linking appetite rules, exclusion matrices, jurisdiction statutes, and cognitive patterns. Every agent decision traces to a governed chunk_id, version, and effective date — not a model weight that may have drifted.