The Problem Platform Products Aurora™ askAurora™ Aurora:GeoStudio® Capabilities Differentiators Use Cases Live Demo C3.ai Request Access

Aurora™ · Intelligence Fusion Platform

Intelligence, fused for decision advantage.

The defining intelligence problem is no longer collection — it is integration. Aurora™ fuses open-source, geospatial, movement, sensor, and infrastructure data into one analytical environment, turning fragmented signals into defensible understanding at operational speed.

Powered by C3.ai
0
Prebuilt data connectors across the C3 AI architecture
0
Languages processed across surface, deep, and dark web
3
Allied operating theaters — United States, United Kingdom, Sweden
24/7
Geo-distributed, hash-partitioned collection network

Aurora in 60 Seconds

See the platform work.

A one-minute film shot inside a live operation — grounded answers, nineteen governed analytic skills, reconstructed movement, and the finished intelligence product.

Plays muted with captions. Use the Sound on control inside the film for narration.

The Modern Intelligence Problem

The problem is not data poverty. It is data separation.

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.

01

Fragmentation distorts analysis

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.

02

The "no known suspect" problem

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 fused.

03

Operational tempo outpaces production

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

From isolated observations to contextualized patterns.

Aurora™ resolves fragmented observations across physical, cyber, geospatial, and informational environments into high-confidence entities, relationships, and risk patterns — a usable, defensible intelligence picture rather than simply a larger one.

Open-source & social signals
Geospatial & movement traces
Sensor & telemetry data
Enterprise & logistics records
Cyber & access-control indicators
Infrastructure & environmental context
Multi-modal entity fusion
Resolved entities
High-confidence objects with provenance & lineage
Pattern & anomaly detection
Pre-operational behavior before it hardens into incident
Evidence packages
Traceable basis for every flagged pattern

Capabilities

Built for questions of pattern and meaning.

Pattern-of-life analysis

Integrate geospatial traces, movement behavior, sensor observations, and reporting history into a complete picture of an entity, network, installation, or area of interest.

Co-location analysis

Surface indirect proximity between entities through shared locations, repeated device presence, and emergent networks not otherwise linked.

Anomaly detection

Identify deceptive or pre-operational behavior — hostile reconnaissance, infrastructure probing, irregular logistics — before it registers as a discrete event.

Multi-agentic engine

Hundreds of specialized agents operate concurrently across a geo-distributed collection network, establishing consensus across multilingual surface, deep, and dark-web sources.

Spatial-temporal sessionization

Advanced sessionization reconstructs fragmented event streams into coherent operational sessions for high-fidelity activity analysis.

Source provenance

Every signal carries source classification, confidence score, and chain of corroboration — explainable outputs grounded in cited evidence.

Key Differentiators

What separates Aurora™ from the alternatives.

The engineering decisions that let Aurora™ run wherever a mission requires.

01

From prompting to delegated autonomy.

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 tests competing hypotheses to counter confirmation bias and returns a complete data-and-tool audit trail, so results can be verified rather than accepted as black-box answers.

02

The Global Collection Network.

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.

  • 17B+daily geolocation points
  • 4.4BSDK MAIDs
  • 6.3BRTB MAIDs
Learn more

Design principles

  • One structure at every scale. A laptop, an air-gapped server, and a multi-region estate share the same layout and behave identically.
  • One identity per request. A collision-resistant, time-ordered identifier is kept unchanged from incoming to results, status, errors, and logs.
  • No central index. Consistent hashing lets any client calculate where a file lives. There is no lookup service to overload or fail.

Deploy anywhere, scale out by configuration

  1. Standalone HFSEdge, air-gapped, and evaluation
  2. ShardedParallel processing, no bottleneck node
  3. Geo-distributedSurvives outages, meets data residency law
  4. Hash-partitionedEven load, predictable routing

What it means for an evaluator

  • Sovereign by configuration. Data can be pinned to a region, a customer data centre, or a disconnected network without a separate product.
  • Same system, any footprint. Pilots and production share one architecture, which shortens accreditation and removes migration risk.
  • Resilience. Replicated shards survive node and regional failures. Requests queue rather than drop during outages.
  • Full auditability. One identifier per request across every stage gives chain-of-custody style traceability.
03

Aurora:GeoStudio® sessionization.

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.

  • 10,795fixes resolved to one ordered path over 30 days
Learn more

The method

  1. 01 · IngestRaw feeds arrive as disjoint packets. Nothing is discarded.
  2. 02 · AnchorEach point is timestamped and ordered. The timestamp governs, not arrival order.
  3. 03 · GroupActivity grouped by time and proximity: one port call, one sortie, one dwell.
  4. 04 · Age offStale attributes are withdrawn rather than presented as current.

Across feeds

  • AIS · vessels. MMSI, position, and navigational status reassembled per vessel into a voyage timeline.
  • ADS-B · airframes. ICAO hex, altitude, velocity, and squawk grouped into one continuous flight.
  • Mobile · devices. Device fixes ordered per identifier into dwells and transits.

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.

04

Commercial reach without classified exposure.

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.

  • 0classified data reaches the provider
  • 80–90%of results discarded locally
  • 100%of transfers human-reviewed
Learn more

Three steps

  1. 01 · Isolated executionObfuscated queries are composed and approved by the analyst before submission, in an unclassified VDI or confidential VM.
  2. 02 · Local controlDLP scanning, save and print restrictions, and audit logging. The original specific query is reapplied to the broad result set.
  3. 03 · Guarded transferSanitized excerpts cross manually, one way only, via ISAFE, DOTS, or a high-assurance CDS guard.

Privacy-enhancing techniques

  • Broadened queries. A 1 km² site widened to a 50–100 km² region over a year.
  • Subquery decomposition. 2–5 innocuous partial queries, intersected locally.
  • Key query generation. Alternative phrasings with no sensitive terms.
  • Noise injection. Plausible dummy traffic with rotated timing.

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.

05

The Aurora™ Inference Engine.

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.

  • 0installs or inference servers
  • 100%offline after first load
Learn more

How offline mode works

  • Offline-complete app. A Service Worker caches the UI and engine, so the app behaves like a natively installed program.
  • 4-bit · 8-bit models. Quantization drops model size sharply, e.g. 2 GB to 500 MB, accelerating the one-time load.
  • No external network. Model files are hosted locally, so even the initial load happens offline or over the LAN.

Load path

  1. 01 · First visitModel files, from megabytes to a few gigabytes, load once.
  2. 02 · StoreTransformers.js and TensorFlow.js store models in Cache API or IndexedDB.
  3. 03 · Return visitsRuns on local CPU, GPU, or NPU, even in Airplane Mode.
06

Source code ships with every installation.

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.

Learn more

Delivery model

  • No vendor intervention. Custom features and urgent patches deployed directly on-site, without third-party scheduling.
  • Lower MTTR. Direct source access and automated testing shorten recovery and feature lead time.
  • No lock-in. Full control of the system, with the option to pull each new release as it lands.

On-site pipeline · customer-owned, trunk-based repository

  1. 01 · CommitFeatures, maintenance, and urgent patches by the customer's engineers.
  2. 02 · QualityStyle checking and complexity analysis (pylint, radon).
  3. 03 · TestManaged test data validates every change.
  4. 04 · BuildSame source, identical binaries and configurations.
  5. 05 · DeployStaging to production via automated and semi-automated pipelines.

askAurora™

Query the fused environment in natural language.

A controlled conversational layer lets analysts pose mission-relevant questions directly against fused data — without manually traversing each underlying system. It lowers the transaction cost of inquiry while preserving the analyst's role in interpretation, validation, and escalation.

  • Retrieve semantically organized outputs across fragmented holdings
  • Deterministic, source-cited responses with preserved access controls
  • Human-in-the-loop feedback adapts the system to mission practice
askAurora™ — Operation Nightwatch
AnalystShow repeated short-duration presence near the three protected sites, cross-referenced with online signaling in the same windows.
Aurora
Querying fused environment across 6 source classes…
Resolved 14 entities · geo-temporal alignment complete
Co-location analysis · 3 shared-infrastructure clusters
Correlating rhetoric with reconnaissance windows
7 NODESNODE-047 shows anomalous burst presence aligned to two intercept windows. Evidence package attached. Recommend escalation to SME Geopolitical.

Operational Use Cases

Where fusion changes the decision.

The same capability — fusing digital and physical signals into a single, governed 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.

The Aurora:GeoStudio® workspace — population-dynamics charts and record counts, a day/hour activity heatmap, an entity-relationship network graph linking device aliases to networks, and a live geospatial map with area-of-interest density clusters and a GeoTools analysis panel.
Live sessionStats · network graph · geospatial map

Aurora:GeoStudio®

The immersive home for location intelligence.

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.

  • Location-timeline analysis, activity density & hotspots, and demographic enrichment
  • Powered by three GeoAPIs — GeoCapture™, GeoCanvass®, and GeoRunDown®
  • Delivered as SaaS, an API analytic feed, or deployed into secure enclaves
Explore the platform & APIs

Decision Advantage

From reactive response to anticipatory warning.

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.

Reduce uncertainty

Narrow the set of plausible interpretations faster and more responsibly by integrating more relevant context into the analytical process.

Improve tempo

Lower the transaction cost of inquiry so analysts, watch officers, and commanders act inside the decision window rather than after it closes.

Increase confidence

Evidence packages preserve lineage and confidence measures, making outputs inspectable and defensible under legal and political scrutiny.

0
Data points processed daily
0
Open sources monitored
<60s
Median signal latency
100s
Specialized models per query

Powered by C3.ai

The enterprise architecture behind operational scale.

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.

C3 AI Type System

A model-driven abstraction that turns disparate feeds — Oracle, Kafka, documents, imagery, time-series — into resolved real-world entities with metadata, lineage, and confidence.

Federated data integration

More than 250 prebuilt connectors span streaming, relational, image, and virtualized modes, with governance and lineage built into ingestion itself.

Data virtualization

A logical abstraction lets sensitive data remain in controlled enclaves — integrate without a multi-year replatforming exercise, and avoid vendor lock-in.

Governed generative AI

Retrieval-augmented workflows separate the model from enterprise data, preserve access controls, and return deterministic, source-cited responses.

Learn how C3.ai powers Aurora™

Governance, Security & Compliance

Capability without governance is a liability.

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.

Privacy-aware by design

Granular role-based access, data minimization, and purpose limitation. Virtualization keeps sensitive data in place rather than copied into central lakes.

Auditability

Reconstruct what data was used, who accessed it, how it was transformed, and why a conclusion was reached — supporting GDPR and allied legal regimes.

Human-in-the-loop

Decisions with operational, legal, or political consequence remain human. Analysts inspect evidence, challenge inferences, and compare source fidelity.

Lawful operationalization

Retention controls, oversight mechanisms, and deterministic, source-cited workflows make every output defensible under scrutiny.

Resources

Data sheets, ready to brief.

Concise, print-ready capability overviews for circulation inside your organization. Open to read, or download to save and print as PDF.

2 pages

Platform Overview

Aurora™ — Intelligence Fusion Platform

The fusion model, capabilities, askAurora™, operational use cases, decision advantage, and governance — powered by C3.ai.

1 page

Product Data Sheet

Aurora:GeoStudio® — Location Intelligence

Platform capabilities, the three GeoAPIs — GeoCapture™, GeoCanvass®, GeoRunDown® — data sources, and mission fit.

6 pages

Technology Brief

Aurora™ Technology Differentiators

The intelligence layer, C3.ai platform, Global Collection Network, GeoStudio® sessionization, Unclassified Access Strategy, Inference Engine, and source code strategy.

1 page

Mission Data Sheet

Aurora:GeoStudio® — Executive Protection

Human-activity intelligence for protective details: who else is on the ground at the residence, route, venue and trip, whether they have been there before, and whether they move with you.

1 page

Mission Data Sheet

Aurora:GeoStudio® — Law Enforcement

From scene canvass to case file: every device present at a scene, ranked by behavior and anchored to a defensible pattern of life. For federal, state, local and task force investigators.

11 pages

Strategic Overview

Sovereign Intelligence — Strategic Overview

Who we are, the Aurora™ intelligence fusion platform, and the capabilities we deliver to national security, defense, law enforcement and commercial organizations.

21 pages

White Paper

Intelligence Fusion and Operational Decision Advantage

The case for multi-source intelligence fusion, using Aurora™ and C3.ai as a case study. Prepared for senior decision-makers in national security, defense and intelligence.

9 pages

White Paper

Critical National Infrastructure Protection

Intelligence fusion for infrastructure security, resilience and civil contingency decision support, using Aurora™ and C3 AI as a case study.

Built for the gravity of the work.

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