Robotics. Done by the model.
Embodied-AI teams rebuild the same scaffolding every time — a MuJoCo or Isaac rig, a randomization script, a perception sim, an RL trainer, a one-off transfer calibration. Aether for robotics is the world model underneath all of it: it forward-rolls contact dynamics, renders the sensors in the loop, trains the policy and tells you — honestly — where the reality gap will hold. SimOS is the simulator your fleet trains and transfers through, not another robotics vendor.
Aether is the AI doing the robotics work.
Three things to know about the AI underneath every workload on this page. We aren't building a chat surface for your team — we are training a foundation model that plans, runs and reports.
The AI does the discipline
Not a chat interface over your engineers. A foundation model that plans the study, picks the method, runs the agents, validates against measured reality and writes the report. The same shape an experienced practitioner would follow — done by the model.
One model, your context
We don't ship a sibling model per industry. The same Aether weights serve every discipline, but the agents on top are trained against your standards, your historical data and your regulatory posture.
Reality is the regulariser
We train on simulation, instrument and design data — not scraped text. The model gets better the more reality it touches. Reality is what tells it when it's wrong.
Strider Robotics.
“The model told us which task wasn't ready before the robot did.”
Took a humanoid manipulation policy from lab demo to factory line in one quarter.
The work, done by Aether.
These are the workloads Aether already runs in robotics. Not a wish-list. Each ships with validated benchmarks and traces a senior engineer can read end-to-end.
- 01
Manipulation
Dexterous and parallel-jaw grasping, in-hand reorientation, contact-rich insertion and tool use — generated and physics-filtered against reach and contact validity.
- 02
Locomotion & whole-body
Bipedal, quadruped and wheeled-legged control with whole-body dynamics, terrain randomization and fall recovery, trained where a real fall costs nothing.
- 03
Sim-to-real transfer
System identification from a handful of real rollouts, residual-physics correction, and an honest estimate of where the policy will transfer and where it won't.
- 04
Synthetic perception
Photoreal RGB, depth, segmentation, tactile and proprioception rendered in the loop — perfectly labelled and consistent with the same physics the controller sees.
- 05
Imitation from demonstrations
Teleop, kinesthetic and video demonstrations replayed, retargeted across embodiments and augmented in sim into a full training distribution.
- 06
Fleet learning & safety
Field failures return as reproducible scenarios; reachability checks and an operational design domain assemble into an evidence-backed safety case.
“We are building the AI that does robotics — not the one that talks about it. Aether doesn't ask your engineers to drive its solvers. It runs the work, validates the artefact and writes the memo.”
The stack today.
The typical stack in robotics — a half-dozen seven-figure renewals stitched together with internal glue code. We replace the spine; we don't touch the niches that work.
The agents in the mix.
Aether coordinates these specialist agents for robotics. Each is independently deployable, but the coordination — and the foundation model underneath — is what makes them more than a folder of scripts.
How we ship into regulated robotics.
The pieces that matter to procurement, security review and the regulator. We ship into industries where the boundary is real and the audit is unforgiving.
ITAR-clean compartments for defence and aerospace work
Export-control gating on agent capabilities by jurisdiction
Sovereign / air-gapped deployments — zero outbound traffic
Reproducible runs signed by model-version hash for design-review
Other companies shipping with us.
A slice of the customers we're allowed to name. The pattern repeats: one workload, one pilot, one comparison memo we co-author.
- Aerospace
Northwind Aerospace
Retired a $1.8M CAE renewal across two quarters.
62%wall-clock reductionRead the story - Drug discovery
Lyrebird Therapeutics
Closed the discovery loop on a fibrosis programme.
9 weekshypothesis → measured hitRead the story - Chip design
Helix Silicon
RTL to signoff on a 4nm SoC — without an incumbent-EDA renewal.
0EDA license serversRead the story
The AI is also running here.
A foundation model that serves twenty-two industries today. The same weights, different agents, different pilot patterns. Browse the ones nearest yours.
Questions about robotics.
What does Aether replace in robotics?
The incumbent stack here — Bespoke simulation rigs, Hand-tuned domain-randomization scripts, Separate perception-sim pipelines, In-house RL training infrastructure and more — collapses into one model and one project file, with Aether for robotics doing the work under one safety story.
What outcomes should we expect?
Sim-to-real (calibrated transfer, not a leap of faith); Unlimited (embodiments · one world model); Per-policy (operational design domain + safety case) — scoped to your workload and measured against your own acceptance criteria.
How does a pilot work?
Three to eight weeks against a workload and a win condition you co-author. We run alongside your incumbent stack on real cases; if we aren't better on the metric by quarter end, the rest of the quarter is on us.
Can it deploy inside our boundary?
Yes — managed, in your VPC, on-prem or fully air-gapped on Aether Cloud, with the audit trail and provenance the regulated parts of this work require.
The AI is ready for robotics.
Send us the workload that hurts. We'll come back with a scoped pilot — three to eight weeks, win condition co-authored. If we aren't better on the metric by quarter end, the rest of the quarter is on us.