Classified imagery is bandwidth-constrained on the way down and a liability once it lands.
RNDA encodes at capture and discards before downlink. Dramatically less to transmit. Nothing classified to store on the ground.
Request a Defense POC →The Problem
Space and defense systems generate massive volumes of sensor data that must be analyzed but cannot be broadly stored. Every copy is a liability. Raw imagery transmitted from orbit is bandwidth-constrained and creates classification exposure at every relay point.
How RNDA Solves It
Satellite imagery proven — 0.98 discrimination gap
Real satellite imagery encoded and queried with 0.98 discrimination gap across 10 terrain and land use types. Forest finds Forest. Residential finds Residential. Submit any satellite image, find the most similar historical scenes.
Edge encoding before downlink
Raw imagery is encoded at the satellite and discarded before transmission. Only 256-byte signatures travel the downlink. Bandwidth reduction is dramatic. Classification liability eliminated.
No classified data store required
The signature store holds no classified content. Queries return similarity scores and signature IDs — never raw imagery. Planetary surface matching without storing planetary data.
Multi-sensor fusion proven
Multi-sensor fusion data encoded at 14,332x compression. LiDAR at 7,460x. Same architecture works across camera, radar, LiDAR, and telemetry streams.
How RNDA Applies
Storage Elimination
192x compression reduces 27,375 TB of daily satellite imagery to ~143 TB, eliminating the need for massive classified data centers. Defense agencies processing 75 TB/day save ~$7.5M/year in storage costs alone.
Privacy Protection
Sensitive geospatial intelligence, target coordinates, and surveillance data are encoded in binary form that is unreadable without authorization. Raw imagery is encoded at the satellite and permanently discarded before downlink — classification liability eliminated at the source.
Compliance Management
FISMA, NIST 800-53, and ITAR data handling requirements are satisfied by ensuring classified imagery cannot be reconstructed without proper chain of custody. RNDA-encoded archives meet DoD data classification standards structurally, not procedurally.
Intelligent Retrieval
Mission planners query semantically across months of satellite archives — finding specific terrain types, infrastructure signatures, or anomalies without decoding the full dataset. Proven on 27,000 real satellite images across 10 terrain types. Discrimination gap 0.98 in ~30ms.
Collaborative Intelligence
Joint task forces and coalition partners access shared intelligence at need-to-know granularity, with RNDA enforcing compartmentalization automatically at the encoding layer. Shared intelligence without shared raw data.
Storage Impact
Industry stat: Defense agencies process 75 TB of satellite imagery per day across 180 command centers, enabling surveillance of 3.2 million square kilometers (Astute Analytica)
27,375 TB × 20% × $276/TB ÷ 192x compression
Defense agency cluster saves ~$7.5M/year — 192x compression on real satellite imagery across 10 terrain and land use types
Proof of Concept Results
Real data. Measured numbers. No synthetic results.
Source: Real satellite imagery — 10 terrain and land use types
What Becomes Possible
"A satellite captures imagery over a planetary surface. The raw imagery is encoded at capture and discarded before downlink. 256-byte signatures are transmitted. Ground systems query the signature store for similar historical terrain — finding geological matches, tracking surface changes, detecting anomalies. No raw imagery ever leaves the satellite."
Ready to see it on your data?
Every number on this page came from a real POC. Yours will be built the same way — against your actual data type, measured compression, real query latency.
Request a Defense POC →