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Robotics · Hybrid

Figure

Figure’s production architecture is centered on its in-house **Helix** vision-language-action stack running on vertically integrated humanoid hardware and a proprietary BotQ manufacturing/software infrastructure, with robots streaming high-bandwidth data for continuous training and fleet improvement[1][2][7][9]. Core control and reasoning have moved off external LLMs to fully in-house Helix models, with cloud services used as supporting infrastructure rather than as foundational AI engines[7][9].

Foundation proximity: Native (own / self-hosted weights)

Foundational models & how they consume them

PrimaryHelix (current VLA stack: 7B vision-language + high-frequency visuomotor policy)· Figure (self-hosted on proprietary training and inference infrastructure) · Native (own / self-hosted weights)

Cloud & datastore

Hybridproprietary manufacturing/operations data infrastructure (MES/PLM/ERP/WMS stack)[2]custom telemetry and training data pipelines for Helix VLA (vision, language, proprioception)[7][9]

Compliance

Not publicly specified; likely standard enterprise practices but no explicit SOC2/ISO27001/IEC 62443 claims in accessible materials[1][2][7][9]

Similar companies

CovariantPhysical Intelligence
Head-to-head: Figure vs CovariantFigure vs Physical Intelligence

Others that build on proprietary / self-built models

Abnormal SecurityAbridgeAdobeAI21 LabsAleph AlphaAmbience

Explore

Native (own / self-hosted weights) →More on Hybrid →

FAQ

Does Figure use a foundational AI model?
Figure uses Helix (current VLA stack: 7B vision-language + high-frequency visuomotor policy) (Native (own / self-hosted weights)).
What cloud does Figure run on?
Figure runs on Hybrid.
What database does Figure use?
Figure uses proprietary manufacturing/operations data infrastructure (MES/PLM/ERP/WMS stack)[2], custom telemetry and training data pipelines for Helix VLA (vision, language, proprioception)[7][9].
How close does Figure run to the foundational model?
Figure is Native (own / self-hosted weights) — close to the metal, so cheaper tokens and more control over outputs.

Sources

figure.ai ↗

Also on the map

proprietary / self-built models

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Architecture inferred from public sources · confidence low · verify before betting on a detail.