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Human-Curated Browser-Use RL Environments

The Browser for Browser-Use RL Environments

Purpose-built to let humans teach agents how to use software — by building computer-use RL environments from real workflows.

Why Model Labs Choose Us

RL Isn't Held Back by Infra — It's Held Back by People Time

We give humans the tools to build environments 10x faster.

Human-guided authoringVisual workflow IDEProduction-safe clones

Building computer-use or browser-use RL environments is brutally time-consuming.

The challenge isn't infrastructure — it's the human cost of creating and curating realistic workflows, edge cases, and verifiable task logic.

Existing tools weren't made for this kind of authoring.

We rebuilt the browser from the ground up to solve this: Wootzapp turns human feedback into live RL environments.

Because we own the browser, every label and correction updates the environment in real time.

The feedback loop closes instantly: annotations become specs, specs become reward logic, and rewards become trainable environments.

wootz-browser

developer@enterprise:~$ # Explore the world's only open-source enterprise browser

$ git clone https://github.com/wootzapp/wootz-browser.git

Cloning into 'wootz-browser'...

✓ World's only open-source enterprise browser

✓ Zero vendor lock-in, full transparency

$ cat README.md | grep -i security

🔒 Enterprise-grade DLP built-in

🛡️ Zero-trust architecture ready

🔍 Every line of code auditable

$ run build --production

Building enterprise browser...

✓ Hardened Chromium base

✓ Mobile-first security policies

✓ Ready for production deployment

Familiar Chromium-based source
Public
Updated now

The world's only open-source enterprise browser. Built on hardened Chromium with enterprise security, mobile-first design, and zero vendor lock-in.

🔓 Open Source

Audit every line

🏢 Enterprise

Production ready

📱 Mobile First

Android native

🛡️ Zero Trust

Built-in DLP

The Wootzapp Browser

A Purpose-Built IDE for Browser-Use RL

Wootzapp is a fully custom browser that records and transforms real enterprise UI sessions into structured, reusable RL environments. Think of it as a simulation IDE for building browser-use and computer-use training grounds.

Clone browser apps into training environments

No code required. Transform real enterprise UIs into browser-use RL environments that agents can learn from.

  • Capture rich user traces across multi-step enterprise workflows
  • Define golden states, goals, and reward signals visually
  • Replay and test agents safely against realistic UIs

Built for human-in-the-loop authoring

The browser handles the complexity so domain experts can focus on curating high-quality computer-use workflows for agent training.

  • Create browser-use RL environments from apps like Jira, Salesforce, Confluence
  • Teach agents to navigate enterprise software safely and efficiently
  • Simulate real-world computer-use workflows for alignment and training
Our Stand

This Is a Human Ops Problem

We believe the next leap in agent performance won't come from better GPUs or simulators — it will come from helping humans build better training environments. Our approach? A new kind of browser, designed from scratch to let domain experts author, simulate, and replay enterprise workflows for agent learning.

Not Infra

Not Evaluators

We're not another infra layer or benchmarking suite. Wootzapp is for the humans who teach agents — the product leads, QA engineers, operators, and domain specialists.

Purpose-Built

Human-Centric RL Authoring

We give them 10x better tools to build browser-use RL environments from real apps — with visual authoring, replay testing, and real-time feedback loops.

From Scratch

A custom browser

Not a Chrome extension or scraper. Wootzapp is engineered from the ground up specifically for authoring browser-use and computer-use RL environments.

Who It's For

For People Training Agents to Use Software, Not Just Chat

If you're building enterprise copilots or autonomous agents that need to interact with real software, Wootzapp gives you the human-in-the-loop tools to show them how — accurately and safely.

Create Browser-Use RL Environments

Transform apps like Jira, Salesforce, or Confluence into structured browser-use training environments for agent learning.

Teach Agents to Navigate Software

Build training grounds where agents learn to use enterprise software safely and efficiently, without production access.

Simulate Computer-Use Workflows

Create realistic computer-use RL environments that capture real-world workflows for alignment and training.

Run Task-Level Evaluations

Test agent capabilities on real UI tasks without modifying production systems or writing complex test harnesses.

Beyond Design

Our browser doesn’t just teach models to design — it can train them on any code that renders.

By running real code inside a real browser, we can turn human judgment into reward signals for more than HTML and CSS.

Expanding the Reward Space

Because our browser runs the actual code, we can define rewards for scenarios where correctness depends on the rendered result.

Every rendered result becomes a measurable event. That’s how we turn the browser into the universal interface for human feedback in codegen RL.

Data visualization

verify chart accuracy, axis scaling, and style.

Automation scripts

confirm DOM interaction, form fills, and task completion.

Markdown & LaTeX rendering

measure readability, formatting, and structure.

Simulation & game logic

reward interactive correctness and frame behavior.

Notebook workflows

check plot alignment, execution flow, and output coherence.

Example environment (news homepage)

Spec locks in grid (`2fr 1fr`), hero ratios, section order, tokens, and policy boundaries. Reward suites check structure, semantics, responsiveness, accessibility, and compliance.

  • Ship as Dockerized RL APIs or Verifiers-ready packages.
  • Scorecards surface structure, token, and accessibility deltas.
  • Every drop includes spec, DSL, and policy versions for audit trails.

Responsive layout

Models practice grids, breakpoints, and spacing with human review loops built in.

Design tokens

Reward functions enforce typography, color, and component tokens your systems rely on.

Accessibility

Specs demand semantic structure, focus states, and motion-safe defaults across viewports.

Reusable modules

Environment DSL keeps cards, rails, and promos composable instead of one-off markup.

Call to Action

Bring Browser-Use RL to Life

Let humans teach agents in environments that actually reflect how work gets done. Wootzapp is how you build them.

Wootzapp — The Browser Built for Human-Guided Browser-Use RL