Aurora™ · Intelligence Correlation Platform
Aurora™ combines grounded generative AI and multi-source correlation to transform cognitive sensemaking, letting analysts rapidly iterate on competing hypotheses with total source provenance.
Aurora in 60 Seconds
A one-minute film shot inside a live operation — source-cited answers, nineteen governed analytic skills, reconstructed movement, and a drafted intelligence product ready for analyst review.
Plays muted with captions. Use the Sound on control inside the film for narration.
The Modern Intelligence Problem
Relevant data exists in abundance, but it is fragmented across systems, disciplines, and security boundaries in ways that impede timely interpretation. Adversaries exploit precisely the seams between open sources, digital infrastructure, physical movement, cyber activity, and environmental context.
When data is distributed across incompatible systems, the burden shifts to analysts to know where to look and how to reconcile contradictory signals — introducing latency, inconsistency, and bias toward known targets over emerging patterns.
The most consequential threats often begin before a named suspect exists — as ambiguous reconnaissance, irregular movement, or subtle pattern-of-life changes. They become visible only when multiple weak indicators are correlated and assessed together.
Border activity, maritime behavior, and hostile reconnaissance unfold on timelines shorter than traditional analytic cycles. Institutions are forced to choose between acting on incomplete information or waiting too long for integrated understanding.
A New Intelligence Layer
Aurora™ resolves fragmented observations across physical, cyber, geospatial and informational holdings into a knowledge graph of entities, relationships and risk patterns, each scored for confidence and traceable to source: a calibrated operating picture analysts can interrogate, not simply a larger one.
Capabilities
Integrate geospatial traces, movement behavior, sensor observations, and reporting history into a structured pattern-of-life baseline for an entity, network, installation or area of interest.
Surface indirect proximity between entities through shared locations, repeated device presence, and emergent networks not otherwise linked.
Surface indicators of deceptive or pre-operational behavior — hostile reconnaissance, infrastructure probing, irregular logistics — for analyst assessment before it registers as a discrete event.
Hundreds of specialized collection agents run concurrently across a geo-distributed network, cross-checking multilingual surface, deep and dark-web sources for corroboration.
Advanced sessionization reconstructs fragmented event streams into coherent operational sessions for high-fidelity activity analysis.
Every signal carries source classification, confidence score, and chain of corroboration — every assertion traceable to cited source reporting.
Key Differentiators
The engineering decisions that let Aurora™ run wherever a mission requires.
Aurora replaces repetitive prompting with delegated autonomy: the operator defines one objective and Aurora runs the full Define–Execute–Verify loop, independently selecting the analytic tools and datasets needed to reach it. Every run applies structured Analysis of Competing Hypotheses to counter confirmation bias and returns a complete data-and-tool audit trail, so analysts can audit the reasoning rather than accept a black-box answer.
A distributed collection and processing fabric built for billions of requests. The GCN is a purpose-designed hierarchical file system that can be sharded, geo-distributed, and hash-partitioned across one or many stores, in cloud object storage, on local disk, or in memory.
Design principles
Deploy anywhere, scale out by configuration
What it means for an evaluator
Sessionization organises raw data points into a coherent timeline, grouping related activity into distinct sessions on time-based criteria. Without it, an analyst holds packets; with it, they hold a voyage, a sortie, or a pattern of life.
The method
Across feeds
Once sessionized, duration, dwell, gap, and change over time become measurable properties. Where a feed goes quiet, the session records a gap; no positions are interpolated.
Classified programs need commercial analytics and GenAI, but querying a commercial provider reveals the site, the window, and the intent. Aurora's Unclassified Access Strategy resolves this with an isolated consumption layer: query broad, filter local, transfer guarded.
Three steps
Privacy-enhancing techniques
The same pattern applies to GenAI: prompts are reviewed before submission, responses are filtered in-session, and only sanitized excerpts move across, never raw prompts or full model outputs.
A zero-installation, browser-based solution that runs AI models on the user's own hardware using WebGPU, WebAssembly, and WebGL. Mission data never leaves the device, no persistent cloud connection is needed after the first load, and there are no inference servers to operate.
How offline mode works
Load path
Every on-site installation ships with its source code alongside Infrastructure as Code, Pipeline as Code, Security as Code, Everything as Code, and Gen AI tooling for mission, workflow, and application creation. Customers operate, maintain, and develop their systems independently. Sovereign Intelligence keeps its advantage through continuous delivery rather than code lock-in.
Delivery model
On-site pipeline · customer-owned, trunk-based repository
askAurora™
A policy-governed conversational retrieval layer lets analysts pose mission questions directly against correlated holdings, without manually traversing each underlying system. Generation is tethered to ingested holdings and the knowledge graph. It lowers the cost of inquiry while preserving the analyst's role in interpretation, validation and escalation.
Operational Use Cases
The same capability — correlating digital and physical signals into one governed, calibrated operating picture — applied across the missions where context decides the outcome: protecting facilities and infrastructure, securing borders and airspace, and resolving who is behind a track. Each case study follows one engagement from the problem to the decision it changed.
Enterprise site security & autonomous robotics — turning on-site patrols into predictive regional intelligence, lawfully.
Read case study
Digital geospatial traces correlated with persistent physical sensing to resolve threats that cross domain boundaries.
Read case study
Wi-Fi, 3D sensors, CCTV, and operational data integrated into one live geospatial picture of a major international airport.
Read case study
Aurora™ + C3.ai widen the aperture around critical national infrastructure — warning before the alarm threshold.
Read case study
Isolating persistently-present devices and exposing foreign telemetry anomalies that indicate location spoofing.
Read case study
A predictive macro-spatial layer for smart communities — verified residents distinguished from recurring unauthorized presence.
Read case study
Closing the loop between a live aerial track and identity, origin, and digital footprint — governed and human-supervised.
Read case studyAurora™ supports counterintelligence and counterespionage missions in operation today. Because these engagements are sensitive, we do not publish them. We are glad to discuss our experience, methods, and supporting source reporting directly with authorized government and partner organizations.
Surface indicators of emerging hostile networks and reconnaissance patterns from weak, fragmented signals — anomalous access, repeated proximity to sensitive facilities, undeclared contacts — before they can be tied to an attributed actor.
Request a confidential briefingDetect and characterize foreign intelligence activity targeting your people, facilities, and infrastructure — surveillance detection, MICE-based recruitment indicators, and telemetry exposure — under strict governance and human oversight.
Request a confidential briefing
Aurora:GeoStudio®
Aurora:GeoStudio® observes over 17 billion geolocation data points every day from 4.4 billion SDK and 6.3 billion RTB mobile advertising IDs (MAIDs) globally — and ingests any location source with a latitude/longitude, from AIS and flight data to telecommunications and passive sensors. Not adtech: proprietary device metadata resolved into movement patterns, recurring locations, density change, and co-location.
Decision Advantage
Reactive systems tell an institution what happened. Aurora™ helps show what may be forming — structured early warning based on pattern analysis, anomaly detection, and contextual correlation, without displacing human judgment.
Narrow the set of plausible interpretations, and state confidence explicitly, by integrating more relevant context into the analytical process.
Lower the transaction cost of inquiry so analysts, watch officers, and commanders act inside the decision window rather than after it closes.
Source packages preserve lineage and confidence levels, making assessments inspectable and analytically defensible under legal and political scrutiny.
Powered by C3.ai
Aurora™ addresses the intelligence problem from the analytic side. C3.ai provides the secure, model-driven platform on which complex cross-domain applications are built, deployed, governed, and sustained — at institutional scale.
A model-driven abstraction that turns disparate feeds — Oracle, Kafka, documents, imagery, time-series — into resolved real-world entities with metadata, lineage, and confidence.
More than 250 prebuilt connectors span streaming, relational, image, and virtualized modes, with governance and lineage built into ingestion itself.
A logical abstraction lets sensitive data remain in controlled enclaves — integrate without a multi-year replatforming exercise, and avoid vendor lock-in.
Retrieval-augmented workflows separate the model from enterprise data, preserve access controls, and return responses with deterministic source attribution.
Governance, Security & Compliance
Legitimacy in this domain depends on necessity, proportionality, lawfulness, and accountability. Governance is built into the architecture and operations from the start — not added afterward.
Granular role-based access, data minimization, and purpose limitation. Virtualization keeps sensitive data in place rather than copied into central lakes.
Reconstruct what data was used, who accessed it, how it was transformed, and why a conclusion was reached — supporting GDPR and allied legal regimes.
Decisions with operational, legal, or political consequence remain human. Analysts inspect sourcing, challenge inferences, and compare source fidelity.
Retention controls, oversight mechanisms, and source-attributed workflows keep every output auditable and analytically defensible.
Resources
Concise, print-ready capability overviews for circulation inside your organization. Open to read, or download to save and print as PDF.
Platform Overview
The correlation model, capabilities, askAurora™, operational use cases, decision advantage, and governance — powered by C3.ai.
Product Data Sheet
Platform capabilities, the three GeoAPIs — GeoCapture™, GeoCanvass®, GeoRunDown® — data sources, and mission fit.
Aurora™ is available to authorized government and partner organizations across the United States, United Kingdom, Sweden, and allied nations. Access is granted by application, beginning with a defined mission problem.
Modular deployment · Pilot to scale · Integration into your existing estate
