Neuromorphic Enclave Architecture
How Rankinog achieves sub-15ms inference latency across 512 continuous spectral bands while maintaining 100% volatile, zero-retention memory guarantees.
Continuous Telemetry Ingestion Pipeline
End-to-end tensor lifecycle in under 15 milliseconds
Streaming telemetry from Sentinel-2, WorldView-3, Landsat-9, airborne AVIRIS, and proprietary LEO constellation downlinks.
Continuous Spatial-Spectral Transformer (CSST) maps contiguous radiance curves from 190nm to 14.5µm, fusing C-Band SAR radar phase shifts.
Executed on NVIDIA H100 SXM5 / AWS Trainium2 SRAM in encrypted memory. Cognitive agent swarms extract vector anomalies and bounding polygons.
Downstream GeoJSON transmitted via HTTP/2 stream. GPU memory is zero-filled immediately. Cryptographic SHA-256 proof of erasure returned.
Hardware-Isolated Zero-Retention Guarantees
In high-stakes aerospace, precision agriculture, and sovereign defense missions, telemetry data is classified intelligence. Standard cloud APIs buffer user inputs for batch inference or training. Rankinog is architected with a strict Zero-Retention Customer Enclave (ZRCE) model:
- ✓ Encrypted Volatile Memory: Telemetry tensors live strictly in volatile GPU SRAM with memory encryption keys rotated per request.
- ✓ Zero Disk Write Guarantee: Raster data is never cached on persistent NVMe or network storage volumes.
- ✓ Never Used for Base Model Training: Your coordinates and operational vectors are mathematically decoupled from base foundation weights.
SageMaker HyperPod accelerated clusters, AWS Trainium2, and Nitro Secure Enclaves.
H100 & B200 SXM5 multi-node InfiniBand fabrics delivering sub-15ms continuous tensor throughput.
Full containerized deployment on customer-owned air-gapped clusters for defense and orbital ground stations.