Sample Efficiency
Reach target scores with 4x fewer samples using our dense rewards.
We bring the environment and the rollout system. Our custom browser renderer and W8 async infrastructure deliver the rewards and throughput you need to train agents for real work.
Give your code generation models eyes. Our renderer generates visual and structural rewards, enabling agents to iterate on UI until it's pixel-perfect.
Train agents on the live web, not static snapshots. We handle the complexity of modern web apps—auth, popups, and dynamic DOMs—so you can focus on reasoning.
Turn any browser game into a reasoning gym. We expose internal game state and provide deterministic frame stepping for high-fidelity RL training.
Evaluate long-horizon search capabilities. Let agents navigate the open web to find answers, with full trajectory replay and ground-truth validation.
researcher@lab:~$ # The interface to your RL environment
$ swe-rl rollout --workers 4 --backend gemini
✓ Userspace reboot (10s) ........... OK
✓ Async batching ................... ACTIVE
✓ CDP reward stream ................ CONNECTED
$ swe-rl evaluate --suite swe-bench-verified
Running evaluation on 50 tasks...
[Env 0] Success: 0.82 (Reward: 0.94)
[Env 1] Success: 0.79 (Reward: 0.88)
$ cat metrics.json | grep -i utilization
"concurrency_utilization": 0.92
"gpu_saturation": 0.88
The only browser built for RL. We expose internal renderer signals to generate rewards that standard browsers can't, all while running 10x faster rollouts.
⚡ 10s Reset
Userspace reboot
🔄 Async Infra
No step barriers
💎 Pure Rewards
Browser-native signals
🛡️ Legit Infra
Production stable
A fully async, emulator-centric rollout system designed to saturate GPUs. Features pluggable scheduling algorithms, userspace reboots, and per-node inference routing.
We are a software company that builds the gymnasium. You build the athlete. Standard browsers are black boxes. We rewrote the renderer and network stack to generate deterministic, browser-native rewards no one else can.
We provide the gymnasium. You build the athlete.
Standard browsers are black boxes. We rewrote the renderer and network stack.
This lets us generate deterministic, browser-native rewards no one else can.
To drive this custom browser, we built the W8 Async Rollout System.
Userspace reboots in 10s. Zero synchronous barriers.
Our goal: Simulate and automate every task in the knowledge economy.
Models are dropped into our environments and tasked with objectives like building features or debugging. We grade their work based on success.
We provide the rollout system because we own the browser. Our W8 architecture delivers the 10s resets and async inference needed for scale.
We're starting with the hardest problem: software engineering. But our infrastructure is built to scale until every task in the knowledge economy can be simulated, graded, and automated.
We don't train models—we provide the reality they learn from. WootzApp integrates natively with inference providers like Together.ai and orchestration frameworks like Ray and CleanRL. You bring the policy and the compute; we supply the massive-scale, interactive browser simulations required to close the loop.
Bypass anti-bot protections and capture frame-perfect rendering events via our hardened CDP pipeline.
Raw speed isn't enough. We provide the scheduling algorithms to make sure every GPU cycle counts.
Maximize task coverage by mixing easy and hard tasks with adaptive horizons. Prevents overfitting while maintaining throughput.
Optimizes for reward-per-second using UCB scores and variance tracking. Perfect for high-efficiency training runs.
Automatic task grouping ensures K trajectories per task for advantage computation, compatible with modern RL algorithms.
DomProgress and visual hash monitoring prevent wasted compute on stuck or looped episodes.
Because we own the renderer, we can grade layout stability, paint events, and network purity—signals impossible to get from Selenium or Playwright.
Our rewards show higher monotonicity and better near-miss separation than standard pass/fail tests. We don't just tell you if you failed—we tell you by how much.
Every pixel, every DOM node, and every network request is part of the grade.
Reach target scores with 4x fewer samples using our dense rewards.
Monotonic rewards that don't plateau, guiding models through near-misses.
Feedback on every render, not just sparse pass/fail flags.
Locked viewports, fonts, and time for reproducible grading.
Run 1000s of concurrent environments with minimal overhead.
Spec locks in grid (`2fr 1fr`), hero ratios, section order, tokens, and policy boundaries. Reward suites check structure, semantics, responsiveness, accessibility, and compliance.
Models practice grids, breakpoints, and spacing with human review loops built in.
Reward functions enforce typography, color, and component tokens your systems rely on.
Specs demand semantic structure, focus states, and motion-safe defaults across viewports.
Environment DSL keeps cards, rails, and promos composable instead of one-off markup.
80% of rollout bugs are systems issues. Run our scorecard to verify throughput, latency, and reliability before you launch a training run.
WootzApp W8 — The Rollout Infrastructure for Browser based RL