EncodingProduct LaunchMay 27, 2026

MForja cuts H.265 video files by 78.6% before encoding

MForja introduces a software shim designed to optimize video infrastructure by conditioning the video signal before encoding, resulting in significant file size reductions (up to 78.6% as demonstrated with H.265). This technology aims to improve efficiency for AI and robotics teams by reducing storage and bandwidth costs for promotional video content. The company highlights its ability to integrate into existing encoding pipelines without requiring changes to downstream systems or codecs.

Key Takeaways

A Figure AI announcement video went from 1.1 MB to 235 KB, a 78.6% reduction.
MForja says the shim works with H.265, H.264, and AV1.
The software conditions the video signal before the encoder touches it.
MForja says it can drop into an existing encoding pipeline without changing downstream systems or codecs.

Why It Matters

For AI and robotics teams shipping commercial video, MForja is targeting a direct storage-and-bandwidth reduction before encoding, not a codec swap. That matters because the article ties the use case to promotional video for Figure AI’s retail deployment announcement, where clips are recompressed across platforms and stored in multiple cloud variants. The broader signal is an infrastructure layer that sits inside current encoding workflows rather than replacing them. Next to watch: whether MForja shows the same size reduction on H.264 and AV1, not just the H.265 example.

StreamingMeme Analysis

Buyers of edge/vision pipelines should treat optimized video infrastructure as core AI cost control—pre-encode reduction and smart transport beat throwing GPUs at raw footage.

StreamingMeme’s take: “AI infrastructure” RFPs that ignore codecs and filtering will overspend. Demand end-to-end bits-per-decision metrics.

Relates to generative bandwidth research and GPU codec support references in this set.