Data Fusion Engine
Ingest or federate structured, unstructured, streaming, document, API, IoT, geospatial and authorized external data.
A governed intelligence operating platform that connects heterogeneous data, models and workflows through an operational ontology so analysts and decision makers can investigate, understand and act from one evidence-based environment.
IntegraIntel models people, organizations, assets, events and relationships as governed objects that can support analysis and operational workflows.
A modular architecture supports investigation, decision intelligence and controlled operational workflows.
Ingest or federate structured, unstructured, streaming, document, API, IoT, geospatial and authorized external data.
Identity matching, duplicate resolution, fuzzy matching and confidence-scored relationship discovery.
Entity relationships, link analysis, graph traversal, temporal links, communities and path analysis.
Map layers, movement analysis, geofencing, spatial clustering, route and proximity analysis.
Event timelines, sequence analysis, historical reconstruction, anomalies and recurring patterns.
Case management, evidence collection, analyst notes, hypotheses, watchlists, tasks and collaboration.
Natural-language investigation, evidence-grounded RAG, entity summaries, relationship explanation and report drafting.
Scenario analysis, prioritization, recommended actions, workflow orchestration and approval-based decision support.
Governed actions and writeback to authorized systems through approvals, policy checks and complete audit trails.
Trace every output back to source, transformation, model version, analyst action and evidence confidence.
Classification, RBAC/ABAC, purpose-aware rules, field/object restrictions, encryption, audit and tenant isolation.
Domain-specific dashboards and workflows for analysts, operators, executives and field teams.
Connect source systems to a semantic decision layer without removing the authority of underlying systems of record.
Reusable ontology and workflow patterns create faster entry points for domain-specific deployments.
Entity, transaction, beneficial-ownership and suspicious-network intelligence.
Identity, device, account and coordinated fraud-network analysis.
Threat actors, domains, IPs, malware, campaigns and infrastructure relationships.
Companies, directors, ownership, affiliations, events and due-diligence intelligence.
Suppliers, routes, facilities, dependencies and geopolitical exposure.
Authorized multi-source intelligence, geospatial context, actor/event analysis and strategic decision support.
Narrative signals become more useful when enriched with entities, organizations, infrastructure, locations and historical events.
Architecture is selected according to source sensitivity, regulatory obligations, operational criticality and client control requirements.
Start from decision workflows and intelligence requirements, then configure data, ontology, analytics and applications around them.