Rankinog AI unifies electromagnetic telemetry across 512 continuous spectral bands—from deep ultraviolet to thermal infrared and SAR radar. Powered by the Hyperion RK-512 transformer with real-time autonomous cognitive agent swarms on zero-retention cloud enclaves.
Toggle between 5 electromagnetic bands in real-time. Drag the interactive split lens to see how standard optical RGB is blind to sub-surface methane leaks, thermal stress, and canopy disease.
Surface appears completely normal under visual RGB spectrum. No chemical or thermal radiance is perceived by standard satellites or human observers.
Notice the localized absorption trough: Sub-surface moisture depletion isolated at -18.4% nominal, with thermal plume vectoring at 1,642nm.
Unlike passive computer vision APIs, Rankinog deploys autonomous cognitive agent swarms that coordinate planetary telemetry ingestion, multi-band vector analysis, and immediate downstream actions without human latency.
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Standard frontier models only understand 3 RGB bands and compress out essential electromagnetic wavelengths. See how Rankinog RK-512 Hyperion compares against legacy systems.
| Model Architecture | Rankinog RK-512 Hyperion | Spectralis CSST-1 | GPT-4o Vision | Claude 3.7 Sonnet |
|---|---|---|---|---|
| Contiguous Spectral Bands | 512 Continuous Bands | 256 Bands | 3 Bands (RGB Only) | 3 Bands (RGB Only) |
| Wavelength Sensitivity | 190 nm – 14.5 µm + SAR | 380 nm – 2,500 nm | 400 nm – 700 nm | 400 nm – 700 nm |
| P95 Inference Latency | < 14.8 ms (Neuromorphic) | 38 ms | 1,240 ms | 980 ms |
| Synthetic Aperture Radar (SAR) | Native Microwave Fusion | Partial Co-Registration | Unsupported | Unsupported |
| Zero-Retention Enclave | Cryptographically Enforced | Enclave Policy | Standard API Terms | Commercial Standard |
| On-Premise / Air-Gapped Deploy | Available for Defense | AWS Only | No | No |
Native client libraries for Python, TypeScript, Rust, and high-performance gRPC. Test the live endpoint right in your browser.
import rankinog
import asyncio
# Initialize with enterprise credentials
client = rankinog.Client(api_key="rk_live_7e8a9f02c4")
async def run_planetary_audit():
# Execute sub-15ms 512-band hyperspectral inference
telemetry = await client.hyperspectral.analyze(
model="hyperion-rk512",
image_uri="s3://rankinog-telemetry/basin_sector_18.tif",
bands=512,
features=["gas_leaks", "canopy_ndvi", "thermal_anomalies"],
sar_radar_fusion=True,
max_latency_budget_ms=25
)
print(f"P95 Latency: {telemetry.latency_ms} ms")
print(f"Detections: {telemetry.anomalies}")
asyncio.run(run_planetary_audit())
// Ready for test dispatch. // Click "Execute Live Test Request" to stream from AWS H100 GPU cluster.
Traditional satellite imagery analysis requires armies of specialized GIS analysts and hours of manual orthorectification. Calculate how much your enterprise saves with automated 512-band cognitive inference.
Replaces 320+ hours of manual raster band stitching per month with continuous real-time API streaming.
High-throughput inference deployed across AWS SageMaker accelerated clusters, sovereign European enclaves, and direct Low Earth Orbit (LEO) satellite interlinks.
Full access to 512-band endpoints for research and prototype testing.
For growing tech platforms requiring sub-15ms continuous telemetry streaming.
Dedicated hardware enclaves, custom fine-tuning, and air-gapped on-premise clusters.
Join climate consortia, precision agriculture leaders, and orbital defense enterprises deciphering planetary telemetry in real time.