Spacetime compiles operating environments for physical AI.

Area, mission, machine, time, and authorized sources define the boundary.

Physical observations and environmental context become bounded, versioned state with provenance, validity, uncertainty, and lineage attached.

Humans govern it, agents query it, and machines operate from it.

The spatiotemporal state engine

Spacetime’s core is a spatiotemporal state engine that makes bounded physical environments addressable across space and time.

It registers physical-world sources to a common spatial and temporal reference, reconciles conflicting evidence, and preserves provenance, validity, uncertainty, processing lineage, and version history.

E(x,y,z,t)

Mission and machine set state, fidelity, and boundary.

Illustrative temporal frame graphOne timeline. Many possible worlds.Valid time says when state applies. Known time says when Spacetime learned it. A run clock maps a simulation into world time without turning it into physical fact.

E_omega(x,y,z,t_valid | known_at=t_known, frame=f)

SIMULATION · WIND SHIFTPossible world. Run time maps to valid time. Never canonical.

Valid: T0 + 30 min
Known: T0 + 10 s
Frame: UTC / Earth-fixed
Evidence: synthetic
Base: env.v42
Run clock: tau + 45 s

Input classesmeasured · reported · derived · reference · synthetic · transformed

Source interfacessensors · data interfaces · platform interfaces · models

GovernanceCanonical → fork → simulate → compare → qualify → accept or reject delta. Only qualified, authorized evidence can create a new canonical version.

One governed operating environment serves the decision chain.

Physical AI teams repeatedly rebuild the same operating-environment stack.

Spacetime turns the shared, non-proprietary layer into reusable edge-capable infrastructure while customers retain control of their sensors, data, models, autonomy software, and mission logic.

Subsystems need local state, platforms need mission-ready operating environments, systems need a shared model of place and time, and systems of systems need a governed environmental baseline.

Platforms coordinating systems of systems need one queryable state across assets and missions.

Machines need bounded local answers, while software agents and AI models need structured state with uncertainty and provenance.

Operators need inspectable environmental state, engineering leaders need one integration surface, and CTOs need infrastructure that can extend beyond one program.

Operating observations become bounded deltas only after registration, reconciliation, and qualification against the prior state.

E_(t+1) = reconcile(E_t, O_t)

Delta E = E_(t+1) - E_t

The resulting state can be queried, compiled, updated, versioned, and replayed across design, simulation, planning, deployment, operation, and analysis.

One operating environment spans platforms, sensors, and sources.

For physical AI companies, Spacetime turns repeated environment engineering into reusable infrastructure across missions, assets, fleets, and programs.

For data providers, authorized sources become machine-usable while attribution, observation time, validity, uncertainty, processing lineage, and version history remain attached.

A physically verified iPhone build uses timestamped regional NOAA wave, wind, and aviation-weather observations plus a tidal-current prediction to drive a procedural Golden Gate operating view while keeping each source’s limits explicit.

A separate local interface exposes recorded NOAA state through six read-only tools and remains local rather than a hosted private broker.

Separately, the public personal site exposes two anonymous read-only tools over one immutable, stale NOAA 9414290 water-level sample; ChatGPT account linking, live phone sharing, and production private authentication remain unverified.

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