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Diffvideo for ML teams

Turn model updates, pipeline changes, and inference improvements into shareable video demos, automatically.

Audience
ML engineers, data scientists, ML platform teams

The problem

ML engineers ship some of the most impactful and complex changes in any engineering organization, but communicating those changes is uniquely difficult. A model accuracy improvement from 91% to 94% is invisible to stakeholders unless you explain what changed, why it matters, and how it affects the product.

How Diffvideo helps

Your repo already has the facts; Diffvideo turns merges and releases into a finished video and a share link, without another recording tool in the stack.

Step 01

Wire GitHub once. On ML PRs and releases we read the diff: model, training, eval, or serving, and turn it into plain-language updates, not a screencast of a notebook.

Step 02

You get a branded MP4 in minutes. Same facts, framed for PMs, leadership, or customers who will not live inside your repo.

Step 03

Rules fire on paths, tags, or labels; or send drafts through the inbox when you want a human on the record before anything publishes.

What you get

Capabilities that line up with this playbook, focused and not a catalog-style feature wall.

Automated video generation

Turns diff-shaped ML work into a narrative about impact and risk: not a readout of tensor names.

Rules engine with smart triggers

Ship when weights, configs, evals, or pipelines change; ignore noise you do not want on camera.

Custom branding

Logo, palette, type: so the file reads as yours in exec email, not as generic SaaS chrome.

Share and embed

Stable links and embed codes for changelog, wiki, or the channel where decisions actually happen.

Start generating videos from your code today

Free to start. No credit card required.