Breakthrough AI Technology

AI-Powered Encoding Efficiency

Breakthrough AI-driven Video & Data Compression for Defense, Aerospace, and Consumer Markets.

Video Compression vs H.265
Lower Latency
No Inter-frame Dependency
Up to 125 FPS
6×–20× Sensor Data Compression
Only Cross-Platform AI Codec
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Why Current Codecs Fail

Sensor Data is Growing Faster Than Codec Technology

Modern defence-grade and 4K/8K sensors generate enormous raw data rates that classical codecs can't handle efficiently. This overwhelms traditional codecs and networks, causing latency, quality drops, and huge storage costs.

SCD Crane MWIR 2560×2048 @ 140 Hz → 1.10 GB/s
SCD Mini-Blackbird MWIR 1280×1024 @ 100 Hz → 1.57 Gb/s
SCD Cardinal SWIR 1280×1024 @ 160 Hz → 2.73 Gb/s

Raw Sensor Data Growth vs Codec Capability

Sensor Data Codec Efficiency

Old Codecs Depend on Fragile Inter-Frame Prediction

H.264/H.265/H.266/AV1 depend on predicting each frame from previous ones. This creates three critical problems:

  • High latency – codec must look at multiple frames.
  • Unstable in real scenes – vibration, rapid motion, occlusions break prediction.
  • Not suited for defence – sudden maneuvers, fast pan, explosions, and poor visibility cause artifacts.

Sentaya's approach is frame-independent, avoiding this long dependency chain.

Traditional Codec – Inter-Frame Dependency

F1
F2
F3
F4

When one frame fails, the whole chain suffers.

Sentaya – Frame-Independent AI Codec

F1
F2
F3
F4

Too Slow for Real-Time Missions

Classical codecs add tens of milliseconds of delay – acceptable for streaming movies, but not for:

UAV video links Missile guidance Satellite downlinks Live ISR feeds Tactical operations

In modern missions, 60–100 ms of latency can mean missed targets, delayed decisions, and reduced survivability.

End-to-End Latency Comparison

100ms
90ms
85ms
25ms
Mission-critical threshold

Classical Codecs Collapse Under Real-World Stress

At very low bitrates, they produce blocky, smeared, artifact-heavy video. Under high motion or vibration, their motion prediction breaks. In darkness, fog, or IR noise, their models fail, losing critical details.

They were designed for clean, controlled consumer video – not for noisy IR sensors on a vibrating drone at 125 fps.

Low Bitrate Performance Comparison

Traditional Codec at Low Bitrate
Sentaya AI Codec at Same Bitrate

Old Codecs Were Built for TV, Not for AI-Driven Systems

Traditional codecs were optimized for TV broadcasting, Blu-ray and OTT streaming, static or predictable content. But modern systems include:

Old World

  • TV broadcasting
  • Blu-ray streaming
  • Static content

New World

  • 4K/8K visible cameras
  • MWIR/SWIR thermal sensors
  • Multi-camera fusion
  • Real-time AI analytics

They must handle multiple sensor streams + AI inference + compression simultaneously – something legacy standards were never designed for.

TV Screen
CameraTraditional CodecTV
EO
IR
Radar
SensorsAI AnalyticsSentaya CodecRF Link / Storage

Too Power-Hungry for Edge and Defence Platforms

H.265/AV1/VVC require heavy compute and energy, which is problematic for drones/UAVs, satellites, missiles, remote ISR outposts, and battery-powered edge devices.

Sentaya is designed for low-power, high-efficiency deployment.

Energy Consumption Comparison

Traditional Codec
Traditional Codec
Sentaya

More compression, less power.

Modern sensors are evolving exponentially. Classical codecs are not. This gap is now the biggest bottleneck in defence, aerospace, and 8K video systems.

AI-Driven Video and Data Compression

AI Video Codec

  • 4× compression vs H.265
  • Ultra-low latency
  • No inter-frame dependency
  • Cross-platform implementation
  • Low energy consumption

AI Data Codec

  • 6×–20× compression for sensor data
  • Lossy + lossless modes
  • Ultra-low latency
  • Designed for medical, aerospace, IoT, defence
Efficiency
Flexibility
Quality
Business Impact

Unique Value Proposition

Better Compression
Lower Latency
Lower Energy
Works on Existing Infrastructure
Cross-Platform (FPGA, GPU, CPU)
Defence-Grade Robustness

Industry-Leading Performance

The only cross-platform AI codec delivering breakthrough compression ratios with minimal latency.

Competitor Comparison

Compression Ratio Comparison

0.9×
1.0×
4.0×

End-to-End Latency Comparison

120ms
100ms
25ms

Mission-Critical Threshold: <50ms

Market Applications

Consumer

Online Video Platforms (Netflix, YouTube)
Gaming / XR / Mobile
8K Smart TVs
Social Media

Defence

Satellites
UAV / Drones
Missiles
Monitoring Systems

Market Size

Consumer $150B
Defence $45B
Other $6B
Total Addressable Market $201B

Roadmap

2025

R&D, Defence Codec Development

Advanced research and development of defence-grade codec solutions

2025

IAI POC

Proof of Concept with Israel Aerospace Industries

Current
2026

Consumer Codec Development, Patent Registration

Expansion into consumer markets and IP protection

2027

Defence Market Entrance

Commercial launch in defence sector

2028

MPEG Standardization, Tech Growth

Industry standardization and technology expansion

2030

Consumer Market Entrance

Full consumer market deployment

Raising Seed Round

Funds will be used to accelerate development and market expansion across defence and consumer markets.

Defence Solution Development

Building Partnerships

Patent Registration

MPEG/ISO Standardization

Commercial Codec Development

Team Expansion

Market Growth

Founders

Daniel Yagudaev, M.Sc.

CEO

  • M.Sc. Signal Processing & ML (FAU Erlangen-Nürnberg)
  • DSP Architect
  • Video Systems FPGA Engineer (Elbit Systems)
  • 15 years at Siemens, Elbit, Fraunhofer

Ruslan Abramov

COO

  • 8 years Project Manager (Hermon Labs)
  • Team Lead (Techaya, Alma Lasers)
  • 14 years in defence & medical

Real-World Validation

Video Codec POC

Proof of Concept with IAI (MATAH Division)

Data Codec Validation

Validated in FDA-approved medical application

ASTRA Program

Part of ASTRA acceleration program powered by Starburst & IAI

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