🧠 AI Lifecycle: Ground Truth → Trusted AI

🛰️ Large language models are brilliant storytellers, but without grounded data they improvise. Satellite intelligence provides the untampered, verifiable source of truth that makes GenAI systems produce beautiful and trustworthy simulations, reliable for real-world decisions.

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APIs • Layers • Embeddings • Real-time streams

Satellite Intelligence → AI Lifecycle → Trusted Systems

🎯 Training & Data Generation

Create high-quality training datasets and reward models using satellite ground truth for superior GenAI development.

🤖 Synthetic Data Generation

Generate realistic training datasets using 64-band LBVM spectral signatures for computer vision and multimodal AI models.

🔬 Cross-validation Framework

Cross-validate LLM embeddings against physics-based satellite measurements for robust model evaluation.

📊 Fine-tuning Supervision

Create domain-specific fine-tuning datasets with satellite supervision signals for specialized AI applications.

🎯 RLHF & Active Learning

Use satellite data for reward modeling, preference learning, and real-time feedback in reinforcement learning from human feedback workflows.

🎯 Reward Signal Generation

Generate physics-based reward signals for RLHF training using satellite measurements as objective ground truth for preference alignment.

🔄 Preference Learning

Learn human preferences by comparing model outputs against satellite-verified reality, enabling continuous improvement through feedback loops.

📊 Active Learning

Identify model uncertainties and knowledge gaps using satellite verification, then generate targeted training examples for continuous learning.

🚀 Post-Training & Deployment

Verify and enhance deployed AI systems with real-time satellite feedback for continuous model improvement and hallucination prevention.

🚨 Real-time Verification

Detect hallucinations in deployed models by cross-referencing outputs with live satellite data for immediate correction and confidence scoring.

📈 Performance Monitoring

Track model performance drift and degradation using satellite benchmarks, triggering retraining when accuracy thresholds are crossed.

🔄 Continual Learning

Enable continual learning in production using streaming satellite data as supervision signal for model adaptation without catastrophic forgetting.

LBVM Use Case Demonstrations

Real-time demonstrations of Large Bio Vision Model APIs with electromagnetic resonance physics and quantum mechanics analysis.

Spatial Intelligence Analysis

Analyze spatial patterns and relationships in urban areas using LBVM spectral analysis

SPECTRAL
/v2/spectral/tiles_lbvm/bangalore/{z}/{x}/{y}.png
Urban Change Detection

Detect changes in urban development over time using temporal analysis

TEMPORAL
/v2/temporal/tiles_change_detection/bangalore/{z}/{x}/{y}.png
Advanced Geocoding

Forward and reverse geocoding with spatial hierarchy analysis

GEOCODING
/v2/geocode/forward
Reverse Geocoding

Convert coordinates to human-readable addresses with spatial hierarchy analysis

GEOCODING
/v2/geocode/reverse
Terrain Analysis

Terrain point and surface analysis with physics-based calculations

TERRAIN
/v2/terrain/point
Terrain Surface Analysis

Get elevation data for an area with configurable resolution

TERRAIN
/v2/terrain/surface
AI Fact Verification

Verify AI-generated facts against satellite ground truth using LBVM embeddings

VERIFICATION
/v2/ai-verification/ai/factcheck
Earth Engine Integration

GPU-accelerated Earth Engine RGB embeddings with customizable band assignments

EARTH-ENGINE
/v2/earth-engine/embedding

See It In Action

The same untampered satellite intelligence available through memories.dev APIs powers Vortx.ai with mind-blowing synthesis quality. Stream this data into AI memory for beautiful and trustworthy simulations.

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LBVM Satellite Intelligence Platform

LBVM

True Color

Natural color visualization (B4/B3/B2)R: B4 • G: B3 • B: B2

Layer Opacity: 80%

Layers
Tools:

Loading map… Ensure API Base URL & Key are configured and Bangalore is preloaded.

Give your AI eyes in the sky.