OPREP collects, organises, correlates, and analyses open-source information in a common operating picture. It combines live data, an entity graph, geospatial views, structured analysis, and locally operated models for decision support.
Analysts need more than another feed. They need a governed system of record for evidence, assessments, and decisions.
Public information is split across aviation, maritime, conflict, humanitarian, cyber, economic, environmental, and social sources. Analysts spend time reconciling feeds instead of assessing the situation.
Signals are often grouped without enough provenance, source reliability, temporal context, or geospatial context. Confidence becomes difficult to explain when decisions move quickly.
Decision-makers need one picture of what is known, where it came from, who can see it, and what changed. Without that control layer, critical context stays buried across systems.
OPREP connects source data, entity relationships, analytic workflows, and reporting in one platform. Assessments remain tied to evidence, provenance, confidence, and the analyst actions behind them.
OPREP evaluates sources, credibility, recency, proximity, and correlation before turning information into an operational assessment.
Public feeds, tracks, imagery, cyber indicators, social posts, and environmental observations enter with provenance intact.
Each source carries standing reliability and information credibility so confidence can be explained.
Entities are resolved, matched by time and location, and linked to incidents, warnings, and campaigns.
Analysts receive evidence-backed outputs with confidence, application classification markings, and audit context preserved.
A continuous workflow ingests public sources, resolves entities, correlates events, and produces intelligence products for analyst review.
OPREP combines open-source collection, graph analytics, vision, controlled agent workflows, and formal reporting on infrastructure you control.
Ingest public aviation, maritime, orbital, conflict, humanitarian, cyber, economic, infrastructure, environmental, advisory, sanctions, social, CCTV, and radio sources. Connectors retain source identity, timestamps, text and media, reliability information, and deduplication keys.
Agent workflows plan, execute, validate, and audit analytical tasks against the intelligence graph. Threat assessment, investigation, correlation, and reporting remain analyst-directed, with approval gates and persisted audit records.
Correlate events using source reliability, information credibility, recency, spatial proximity, semantic similarity, and evidence diversity. OPREP resolves duplicate entities, creates incidents, evaluates warnings, and links evidence to every assessment.
Generate IIR, INTSUM, INTREP, SITREP, SPOTREP, SALUTE, STANAG 2022, and investigation reports from governed source context. Products carry source evaluation, confidence language, application classification markings, and trigger provenance.
Evaluate configurable warning patterns across entities, tracks, source reliability, spatial proximity, and temporal recency. OPREP surfaces warnings only when required evidence conditions are met.
Persist entities, relationships, annotations, assessments, and source evidence in a searchable graph. Analysts can traverse links, explain connections, detect structural anomalies, and inspect how entities evolve over time.
Send images attached to entities and social posts to Geo Analysis, or provide an uploaded file or image URL. The local vision model returns ranked location predictions with confidence, plots the result on the map, and can create a Location entity for follow-on analysis.
OPREP turns governed source context into formal reporting formats with source evaluation, confidence language, and application classification markings preserved.
OPREP is designed for on-premises deployment with locally operated text and vision models. Model endpoints are configurable, and optional external backends can be disabled in air-gapped mode.
Run text, vision, tool-calling, enrichment, summary, and embedding workloads through locally operated model services. Model servers can run on the application host or elsewhere inside the deployment boundary.
Air-gapped mode disables optional external model backends. Local data and models remain available, while internet-dependent feeds require connectivity to receive updates.
Use Docker Compose for development and single-host deployments or the included K3s manifests for Kubernetes. Application data can use a local or mounted storage path selected by the deployer.
UK classification markings, role-based permissions, clearance filtering, approval gates, and audit logging control application access. Deployers remain responsible for accreditation and data handling.
OPREP is not a hosted SaaS product. It is deployed inside an infrastructure boundary selected and operated by the deployer.
The repository contains the platform code, deployment configuration, documentation, security policy, contribution guidance, and development setup.
