Embodied AI
for the humanoid
era.
ALVPHA Tech develops an ARM-native, hardware-agnostic embodied AI framework for humanoid robotics — one coherent stack from NVIDIA Grace Blackwell training clusters to Jetson Thor edge deployment.
One stack,
edge to data
center.
The next generation of robotics is no longer hypothetical. Figure, Boston Dynamics, Agility, Tesla Optimus, Unitree and 1X are scaling humanoid platforms toward commercial deployment between 2026 and 2028.
But the AI stack behind these robots remains fragmented. Training happens on x86 datacenter GPUs. Deployment runs on ARM edge silicon. Every transition costs engineering effort, introduces quantization drift, and burns energy that mobile humanoids cannot afford.
ALVPHA Tech eliminates this gap. Our framework runs natively on ARM throughout — from training on NVIDIA Grace Blackwell to inference on Jetson Thor, with energy efficiency as a first-class design constraint, not an afterthought.
Who is building ALVPHA.
“Humanoids will move from labs into production between 2026 and 2030. Whoever owns the stack then shapes the next two decades of robotics. ALVPHA Tech is our answer — built in Germany, designed for the world.”
Built on NVIDIA. Extended by ALVPHA.
Hardware
- →NVIDIA Jetson AGX Thor — edge / deployment, 2,070 FP4 TFLOPS, 128 GB unified memory, ARM Neoverse V3AE.
- →NVIDIA DGX Station GB300 — R&D, 784 GB unified memory, 20 PFLOPS FP4, Grace Blackwell Ultra.
- →Grace Hopper cloud burst — Nebius EU, CoreWeave, for peak training workloads.
Frameworks
- →NVIDIA Isaac Lab + Sim — simulation and synthetic data generation.
- →NVIDIA GR00T (N1.5) — foundation Vision-Language-Action models for humanoids.
- →TensorRT-LLM + NIM — optimized inference and microservice deployment.
- →LeRobot · ROS2 · MuJoCo — open-source integration layer.
ALVPHA Memory Core + Energy Optimization Layer
Long-term agentic memory and knowledge representation for embodied agents operating across extended timeframes.
Joules-per-inference profiling, policy compression, and runtime adaptation for mobile compute envelopes.
Hardware-agnostic deployment target — Jetson Thor today, extensible to next-generation ARM edge silicon.
Three phases. From simulation to production.
Validation
Open-hardware integration on SO-ARM101 + Jetson AGX Thor. MuJoCo simulation pipeline. ACT and Diffusion Policy training for manipulation tasks.
FUNDING: ZIM · FORSCHUNGSZULAGE 2026
ADAM.
Proprietary humanoid development platform. GR00T-based VLA fine-tuning at scale on DGX GB300. First commercial pilots with German Mittelstand integrators.
FUNDING: EIC ACCELERATOR · INVEST BW · STRATEGIC PARTNERSHIPS
EVE.
Production-grade humanoid AI brain. Framework licensing to robotics OEMs. Multi-robot orchestration and fleet management.
FUNDING: SERIES A / STRATEGIC PARTNERSHIP TRACK
Building in public.
We're building ALVPHA as an open research pipeline. Demos, technical updates, and roadmap progress shared publicly — so partners, investors, and talent see what's being built, in real time.
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German R&D. European ambition.
ALVPHA Tech GmbH is a German research and development company headquartered in Germany, focused on agentic AI, multimodal architectures, knowledge representation, embodied intelligence, and energy efficiency.
The company operates as a wholly-owned subsidiary of ALVPHA Holding GmbH (HRB 751537, AG Ulm). The corporate structure and Unternehmensgegenstand are notary-confirmed and optimized for German and EU research funding programs — ZIM, Forschungszulage, EIC Accelerator, and Invest BW.
The ALVPHA trademark is registered with the European Union Intellectual Property Office (EUIPO).
Let's build the embodied future.
We work with robotics OEMs, industrial integrators, research institutions, and funding partners. If you build humanoids — or fund them — let's talk.