Building the infrastructure
embodied agents deserve
Open-core runtime infrastructure for governed embodied deployment.
AEROS builds the runtime layer that turns embodied AI from lab demos into governed, production-grade systems. We make deployment safe, auditable, and continuous.
We build governed, evolvable runtime infrastructure for embodied agents.
Not another robot OS. Not another model wrapper. A runtime platform that closes the gap between "AI demo" and "AI in production" — making it manageable, safe, and auditable for every deployment.
A runtime, not a demo
AEROS started from a single observation: the gap between "AI demo" and "AI in production" for embodied systems isn't a model problem or a hardware problem. It's a runtime problem.
So we built one. AEROS is the governed runtime layer that sits between the LLM planner and the actuator — handling identity, persona, capability evolution, audit, and rollback for agents that need to run continuously, safely, under governance, in the real world.
Today, AEROS is an open-core runtime with an Apache 2.0 core, a growing capability packaging system, and an enterprise governance layer. We're based in Sydney.
Why embodied agents need runtime infrastructure
Models are necessary but not sufficient
Foundation models give agents the ability to reason. But reasoning without governance, state management, and lifecycle control is a demo, not a product.
Hardware diversity is accelerating
Humanoids, quadrupeds, AMRs, drones, collaborative arms — each with different capabilities. Capabilities must be modular, portable, and versionable.
Production demands governance
In warehouses, hospitals, and public spaces, "what happened?" and "who authorized that?" are not optional questions. Runtime governance makes them answerable.
The timing is right
Models are ready
Foundation models can now reason about physical actions, objects, and environments. The intelligence layer is no longer the bottleneck.
Hardware is diversifying
Humanoids, quadrupeds, AMRs, collaborative arms — the fleet is getting heterogeneous. A shared runtime layer is no longer optional.
Governance is becoming unavoidable
As robots move from labs to warehouses, hospitals, and public spaces, policy enforcement, audit, and accountability become regulatory requirements, not nice-to-haves.
Thesis-driven, engineering-first
Most robotics infrastructure is built bottom-up from middleware. AEROS is designed top-down from a governance-first thesis and implemented as production-grade open-source software.
Single-agent thesis
A clear architectural principle that every design decision traces back to — one identity, one runtime, one audit chain.
Open-source MVP
Not slides. Running code under Apache 2.0, with a passing test suite and a measured benchmark.
Governance is the wedge
The runtime layer between the LLM and the actuator is where audit, persona, and rollback have to live — and where the commercial value sits.
Milestones
AEROS open source MVP
Runtime Core released under Apache 2.0 with a passing test suite and measured benchmarks.
v0.11.0 partial — hardware + bench v2
Real-hardware adapter seams for Unitree G1 and Franka Panda; multi-LLM benchmark matrix with public leaderboard.
Runtime Core v1.0
Production-ready runtime with full lifecycle management, ECM support, and tracing.
First pilot deployment
Proof-of-concept deployment with a warehouse automation partner.
Governance Console launch
Enterprise governance product for fleet-scale policy enforcement and audit.
For investors and partners
AEROS is defining the governed runtime layer for embodied AI — a systems category that doesn't exist yet. We're looking for partners who understand infrastructure plays and are willing to invest in the platform layer.