ArcheBase builds the
operational data layer
for Physical AI.
We turn real robot episodes into operational data assets and expose physical compilation capabilities through Data APIs.
The bottleneck is no longer the model alone, but stable, scalable, high-quality operational data.
「 Evolutionary Data Loop 」
Robots need operational data,
not just observational data.
Observational data records what happened. Operational data captures the actions, states, contact, and failures that make robot learning possible.
Ego Data for Physical AIRaw Inputs
01Observational data records what happened: images, trajectories, logs, and state changes.
Compiled Assets
02Operational data captures how to act next: contact, task stage, failure cause, recovery, and quality rules.
「 Productized Output 」
We build the output:
operational data assets and callable physical intelligence.
The conversion from observational data to operational data becomes a product: assets teams can train on, evaluate with, query, and call through Data APIs.
Data Assets
Operational data for training and evaluation
Compiled task datasets, benchmarks, scenario packages, evaluation assets, and reusable templates.
Intelligence as a Service
Physical compilation capabilities, exposed through Data APIs
Call task retrieval, failure diagnosis, evaluation generation, quality checks, and version tracing through the Physical Causal Model.
「 Data Compiler 」
The compiler is how observation becomes operation.
The compiler combines physical-causality modeling and data engineering, turning raw episodes into operational data assets and model capabilities that Data APIs can call.