In development · web apps first
Local AI made easy for builders.
Add AI features that run in your users’ browsers. Model Roll is being built to handle the runtime, compatibility, updates and rollback.
Keep the AI
in the browser.
Cloud AI can get expensive, and sending user data away creates privacy tradeoffs.
Runs on the user’s device
Supported tasks run client-side once the model loads.
Data stays in the browser
Audio, images and documents don’t leave it for supported tasks.
Built on web standards
WebGPU, WebAssembly, Web Workers and browser storage.
Planned. Exact browsers, runtimes and fallbacks are published only after testing. Browser AI guide
Start with a feature.
Not a model file.
Choose what users need to do. Model Roll handles the AI underneath.
Speech to Text
Turn spoken words into useful text.
Captions, dictation or transcripts, with the audio processed in the browser.
A meeting tool that turns a recording into an editable transcript without uploading the audio.
Search & Match by Meaning
Find the right result, not just the right word.
Help users find related notes, documents or products even when they use different words.
“refund for a damaged order”
It matches“The customer asked for their money back because the package arrived broken.”
Understand Images
Make images part of the workflow.
Classify images, detect objects, or select a subject, without the image leaving the browser.
A product-photo editor that removes the background before a listing goes live.
Read Documents & Extract Data
Turn documents into usable fields.
Read supported documents and draft fields for the user to check.
An expense tool that drafts the merchant, date and total from a receipt.
Understand & Organize Text
Less sorting. More useful information.
Summarize, label or extract details: one focused task, not a general chatbot.
A notebook that summarizes a saved article and suggests a category.
Translate Text Locally
Help users across languages.
Translate between supported language pairs once the model has loaded.
A travel planner that translates saved phrases with a weak connection.
Find & Hide Sensitive Details
Add a review step before sharing.
Flag emails or phone numbers for removal, then let the user review. Not a guarantee of full anonymization.
A sharing tool that highlights contact details and asks what to hide.
Planned capabilities. Each combination is tested before it’s supported.
Five steps.
You stay in control.
From your repo to a reviewed release, and around again for every update.
- 01
Connect your repo
Pick the web app repository Model Roll may work with.
- 02
Pick a feature
Choose a capability and the browsers that matter.
- 03
Check the fit
See the runtime path, fallbacks and limits before any code changes.
- 04
Get a pull request
The integration and its tests arrive on a separate branch.
- 05
Review and ship
You review the pull request, merge and release.
- Then around again
Every update, the same loop
Model updates, compatibility fixes and rollback come back through these five steps.
Hands on.
Or agent assisted.
Work in the dashboard and CLI, or let Codex and Claude Code follow the same plan.
Your repo, your review
Changes arrive as a pull request. Nothing ships without you.
Operations after the demo
Compatibility fixes, model updates and a path back to the last good release.
DevTools companion
See the runtime, cache and fallbacks in Chrome and Edge.
Integration tools and the DevTools companion are in development, not yet available to install.
Questions
What is local AI for a web app?
The AI task runs inside the user’s browser instead of sending every request to a hosted AI provider. A model still needs to load, and some account, download, or update work can require the internet. Read the plain-English browser AI guide.
Which browsers will you support?
The first release is focused on web apps. Exact Chrome, Edge, Firefox, Safari, device, runtime, and fallback support will be published only after testing. Native iOS, Android, macOS, and Windows work is preserved for later expansion, not promised for the first release.
Is Model Roll another JavaScript AI runtime?
No. Model Roll is the repository-to-production integration and operations layer. It plans, prepares, tests, and maintains a supported runtime path rather than inventing another general-purpose inference engine.
Does “open-weight” mean “local”?
No. Open-weight describes access to model weights. Local describes where inference runs. A model can have accessible weights and still be hosted in the cloud, while a compatible model can run locally in the browser.
Is this only for experienced developers?
No. Model Roll is being built for developers, indie builders, small teams, and people building with AI coding tools. The main path stays in plain language; technical detail remains available when needed.
Can I bring my own model?
Compatible models and supported custom adapters are planned. They still need to fit a supported task, browser runtime, licence, download size, and performance envelope. Training and fine-tuning are outside the first release.
How will pricing work?
Model Roll is planned as a paid subscription for integration and ongoing operations. Prices and limits will be published before launch. Customer-owned compute, storage, and build systems are the default where they preserve the experience; any separate provider costs will be explained.
Will cancelling break my users’ apps?
No. The planned licensing approach does not remotely disable already-shipped local AI or downloaded models. New managed integrations, releases, and ongoing services depend on an active subscription. Full terms will be published before purchase.
Follow the web release.
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