HUD is infrastructure for building reinforcement learning environments: run agent workloads at massive concurrency, capture traces, benchmark models, and turn production systems into RL-ready training signals—without brittle one-off tooling.

Frontier labs training specialized agents, product teams deploying agents against real systems, and researchers who need rigorous evaluation at scale. Use the free SDK locally, burst into the cloud when you want parallel instances and telemetry.

Does HUD support reinforcement learning?

Yes. HUD is built around environments, scenarios, and traced rollouts—the same primitives you need for iterative RL workflows, benchmarking, and high-signal datasets for labs.

How do environments work on HUD?

Define tools and scenarios with the hud-python CLI, iterate locally, then run at scale with parallel sandboxes and live debugging. Compatible with typical agent stacks and inference clients.

How can I integrate HUD with my stack?

Install the hud-python tooling, plug in OpenAI-compatible clients at inference.hud.ai for tracing, or talk to us for enterprise onboarding, SOC 2 needs, or volume deployments.

HUD — Build RL environments

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HUD x YC RL for RSI and Autonomous Businesses Hackathon | June 21–22

The platform for building RL environments

Encode your expertise into environments to train and evaluate models,and create the post-training data that aligns AI to your work.

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Task Runs1.3M+

Environments Created2,500+

Inference Calls15M+

Infrastructure for aligning AI to the real world.

The previous generation built apps to impact the world.This one builds the environments that align AI to it.

Create trainable environments at scaleRun agent tasks at scale over thousands of concurrent environments and manage your taskset results with ease.

Turn environments into revenueSell to research teams on HUD vendor marketplace.

Investigate your environmentsDebug agent behavior and improve reward signal by understanding what's actually happening.

QA your tasks automaticallyOur agents audit every trace for grader mistakes and reward hacking before they corrupt your tasks.

Failure AnalysisSurfaces every problem behind a failed run with evidence and a code-level root cause — not just a one-line label.

Prompt-Grader AlignmentVerifies the grader's checks line up with what the prompt actually asks for, so evals judge the right behaviors.

False Negative DetectorCatches unjustified failures — the agent actually solved the task, but the grader scored it wrong.

False Positive DetectorSpots passes that aren't really passes — the agent got credit without genuinely completing the task.

Reward Hacking DetectorFlags traces where the agent gamed the eval — test manipulation, output hardcoding, scorer exploits.

Failure AnalysisSurfaces every problem behind a failed run with evidence and a code-level root cause — not just a one-line label.

Prompt-Grader AlignmentVerifies the grader's checks line up with what the prompt actually asks for, so evals judge the right behaviors.

False Negative DetectorCatches unjustified failures — the agent actually solved the task, but the grader scored it wrong.

False Positive DetectorSpots passes that aren't really passes — the agent got credit without genuinely completing the task.

Reward Hacking DetectorFlags traces where the agent gamed the eval — test manipulation, output hardcoding, scorer exploits.

Customer stories

DoorDash

How DoorDash ships production agents with confidenceDoorDash evaluates and trains its production agents against workflows from real menu and support operations, tightening grounding and retrieval before anything reaches a customer.

Coming soon

Sharpe

How Sharpe scales high-quality RL environmentsSharpe designs RL environments for coding, AI training, and ML project management using HUD, with full QA on every task they make to ensure the highest quality training data.

Coming soon

UiPath

How UiPath benchmarks enterprise agents against every frontier modelUiPath brought its UI-CUBE enterprise computer-use benchmark onto HUD, where its own agents and every frontier model are measured against the same enterprise workflows.

Coming soon

Pricing

SDK + Platform AccessFree

Turn any software into agent tools

Define scenarios for evaluations

Compatible with any agent framework

Cloud$0.25 / environment hour

100+ parallel environment instances

Live telemetry and debugging

Detailed trace analysis

Get $10 in free credits

EnterpriseCustom pricing

Train agents on your environments

SOC 2 compliant infrastructure

Volume pricing and dedicated support

Are you a student or researcher? Get $100 in free credits with a .edu email.

Frequently asked questions

Who is HUD for?

Does it work with any model?

Can I train a model on my own environments?

What are HUD QA Agents?

Can I monetize environments I build?

Is HUD open source? How do I get started?

Build environments that frontier labs trustCreate your first environment in minutes. No credit card required.

Frontier-grade evaluations, environments, and training data for AI labs.

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