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SimTooReal
Train robots in any sim. Ship to real world. Two commands.
Sim-agnostic robot RL training infrastructure. One platform for IsaacLab, MuJoCo, Gazebo, and LeRobot — live dashboard, GPU pool, Robot Studio, and zero lock-in. Your code, your sim, your checkpoints.
Hey Product Hunt! 👋
I'm Vardhan, and I've been building robotics training infrastructure for the past year.
The frustration that led to SimTooReal: I was running the same policy on IsaacLab AND MuJoCo to cross-validate results — and I had five different terminal windows, three different logging formats, and no single place to compare reward curves side by side. Every team I talked to had the same duct tape.
W&B is great for ML broadly, but robotics has specific needs: body telemetry (CoM height, joint torques, base velocity), episode failure clustering, sim-to-real eval, and multi-environment dispatch. None of that fits cleanly into a generic experiment tracker.
So I built the missing layer. Two commands, your existing training script unchanged, full observability across every major sim.
The thing I'm most proud of today is Robot Studio — you describe a robot task in plain English, Claude generates the training project files, and you click "Run on GPU." Zero infrastructure setup. It's the fastest path from "I want to train a bipedal walker" to actual training curves I've ever seen.
We ran brutal benchmarks on an A10G: Ant-v4 on MJX 4096 envs hit 2,684 reward. We traced a bug where per-env Python loops triggered 40,960 GPU→CPU scalar transfers per update (10+ min/iter). Fixed to 3 transfers. Now it's fast.
I'd love your feedback on:
→ What sims/frameworks are you stuck on that we don't support yet?
→ What's the #1 thing missing from your current RL observability stack?
Try it free: simtooreal.com
CLI: pip install rpx-agent
About SimTooReal on Product Hunt
“Train robots in any sim. Ship to real world. Two commands.”
SimTooReal was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #17 on the daily leaderboard. Sim-agnostic robot RL training infrastructure. One platform for IsaacLab, MuJoCo, Gazebo, and LeRobot — live dashboard, GPU pool, Robot Studio, and zero lock-in. Your code, your sim, your checkpoints.
On the analytics side, SimTooReal competes within Robots, Developer Tools and Artificial Intelligence — topics that collectively have 995.6k followers on Product Hunt. The dashboard above tracks how SimTooReal performed against the three products that launched closest to it on the same day.
Who hunted SimTooReal?
SimTooReal was hunted by Vardhan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of SimTooReal including community comment highlights and product details, visit the product overview.
Vardhan