About Hardsim
Making robotics simulation easier, better, and production-ready.
Make Simulation Easy and Better
Hardsim is built to make robotics simulation simple, reliable, and scalable for real teams. We provide a unified API and Python SDK to launch simulation jobs, orchestrate managed training runs, and operate large workloads without friction.
Our goal is to help teams spend less time fighting infrastructure and more time improving robot behavior, policy quality, and sim-to-real performance.
Parallel submissions per group
Simulation and training
What We Build
A cloud control plane that accepts simulation jobs, submission groups, and managed training runs; provisions headless GPU workers; captures events, artifacts, and checkpoints; and exposes everything through the dashboard and API.
The Problem We Solve
Robotics teams lose months to infrastructure: worker orchestration, queueing, retries, data movement, and cost reconciliation. These infra concerns slow iteration more than model work. Hardsim standardizes this runtime layer so teams can iterate on tasks, rewards, and controllers faster.
Who Uses This
Robotics companies, embodied AI labs, and simulation platform teams running Isaac Sim and MuJoCo style workloads, synthetic data generation, and reinforcement learning loops at production scale.
How It Works
Submit
Define robot and environment payloads, then submit simulation jobs or training runs via SDK/API. Use single-submit or typed submission groups for high-volume dispatch.
Orchestrate
Hardsim schedules compute, provisions GPU workers, manages retries, and transitions states automatically across queued, running, and terminal stages.
Execute
Headless simulators run rollouts and trainer steps with checkpoint lineage, structured events, and machine-readable error categories for reliable automation.
Retrieve
Download artifacts, metrics, manifests, and checkpoints from the dashboard or API, and track exact-second usage settlement with run-level billing visibility.
How We Build
Reliability First
Every workload stage is evented and observable, with clear terminal states, checkpoint lineage, and machine-readable failure reasons.
API-Driven By Default
The SDK and API are the source of truth for workload execution, while the dashboard focuses on visibility, controls, and operational debugging.
Cloud Platform
Usage-based platform with exact-second settlement for simulation and trainer compute. Teams run jobs and managed training loops without operating their own orchestration stack.
Enterprise
Custom SLAs, dedicated compute pools, network and security controls, and workflow integrations for organizations running high-scale production robotics programs.