Cut Your Data in Half. Your Models Won't Notice

Reduce storage costs with ML-Safe compression. Proved across the AV data lifecycle, for real-world and synthetic video

Talk to our team See how it works

Cut Your Data in Half. Your Models Won't Notice

Reduce storage costs with ML-Safe compression. Proved across the AV data lifecycle, for real-world and synthetic video

Talk to our team See how it works

Trusted by giants

Trusted by giants

How it works

Compress smarter, not harder

Beamr's patented Content-Adaptive Bitrate technology (CABR) evaluates each frame to apply maximum compression while preserving ML accuracy. Supports any major codec, GPU-accelerated, and deployable with no changes to your existing pipeline

Works on already-encoded video — no re-ingest

Standard output: H.264, HEVC, AV1

Runs on NVIDIA GPUs already in your stack

Deploy via Docker, API, FFmpeg, or managed cloud

Proven results

Benchmarked on real-world AV data

We validated ML-Safe against PandaSet and standard YOLO-based benchmarks using the Cosmos pipeline. Real-world results prove that aggressive compression maintains object detection accuracy while dramatically reducing file sizes.

Read the full benchmark results →

48%

avg. size reduction

< 2%

mAP difference

41–57%

Cosmos pipeline

PSNR ✓

quality confirmed

Camera / Sensor Ingest

Encode (H.264 / HEVC)

CABR Optimization

Storage / ML Training

Zero disruption

Fits your existing pipeline

CABR integrates seamlessly into your H.264 or HEVC encoding pipeline without disruption. Sit between encode and storage stages to optimize bitrate while maintaining compatibility with existing workflows.

Every dataset is different. Let's explore yours.

Tell us about your data and we'll provide compression estimates, ML accuracy validation approach, and integration roadmap tailored to your needs

Compression estimates for your pipeline

ML accuracy validation approach

Integration roadmap

Tell us about your data

We'll get back within one business day.

No commitment required.