Explore three reference implementation patterns for connected financial data and AI. These are illustrative delivery approaches, not client case studies or measured production results.
Situation: conflicting identifiers across market feeds and internal systems.
Delivery pattern: identity ontology, mapping rules, provenance and SHACL constraints, activated through a queryable graph.
Evidence: traceable identifier resolution, unresolved-case report and reviewed competency questions.
Situation: analysts need answers across filings, events and portfolio context.
Delivery pattern: event and evidence ontology, entity linking, GraphRAG retrieval policy and citation path.
Evidence: question set, source coverage, retrieval trace and human evaluation protocol.
Situation: security events are disconnected from financial services and obligations.
Delivery pattern: technology dependencies, threat concepts, controls and business impacts connected across ontologies.
Evidence: explainable impact paths, control gaps and reviewed scenario outcomes.
Build an evaluation around the questions your users need to answer.
Can a reviewer follow the answer back to the source material and verify that it supports the claim?
Does the proposed approach improve the agreed question set compared with your current workflow or a simpler baseline?
Review latency, operating cost, permission enforcement, maintenance and ownership before deciding to expand.
We link the business question, ontology scope and validation method from the beginning.