The Common Operational Data Architecture is deployed across the most demanding mission environments in the world. Here's how operators use it.
Partner Nation Data Sharing
Two allied intelligence organizations need to share OSINT and signals data in near real-time, without trusting each other's networks or identity providers.
Catalyst's cryptographic data fabric establishes a federated trust boundary that lets both organizations contribute and consume data without exposing internal infrastructure. Each party maintains sovereign control of its own data and grants only the access it approves. Discovery surfaces shared intelligence feeds into unified analyst workspaces — without any data ever crossing into a foreign network unencrypted or without explicit authorization.
A joint task force needs unified situational awareness across classified, partner, and open-source data — with no common infrastructure and multiple incompatible identity systems.
CODA's full stack operates across classification boundaries simultaneously. Catalyst federates data sharing across disparate organizations with no shared infrastructure required. Pulse ingests streaming sensor data, partner feeds, and classified collection in a unified processing pipeline. Discovery delivers a single analyst interface that queries across all tiers — presenting a coherent operational picture regardless of source classification or network boundary.
An analyst team needs to answer intelligence questions in minutes, not days, drawing from hundreds of open sources simultaneously.
Discovery provides a natural-language query interface over structured and unstructured open-source data — news feeds, social media, public records, academic databases, and more. Powered by Orbis AI, it synthesizes multi-source answers with citations and confidence levels. Pulse maintains persistent monitoring pipelines that alert analysts when conditions change, so teams stay current without manually reviewing every source. The result is an analyst workflow measured in minutes, not shift cycles.
A government agency wants to deploy AI on sensitive data without sending it to commercial cloud providers or accepting third-party model access to classified information.
CODA deploys entirely within customer-controlled infrastructure — on-premise, air-gapped, or in a dedicated government cloud enclave. Catalyst governs which data the AI can access, applying policy-based controls that never permit raw data to leave the boundary. Pulse runs the AI inference pipeline locally, with model weights and customer data remaining inside the classification boundary at all times. No telemetry, no model training on customer data, no phone-home requirements.