01
Neural and Generative AI assist
They can interpret unstructured inputs, find patterns and propose possibilities. Their output is useful, but it is not yet an approved engineering answer.
Symbolic AI · Physical AI
AI can generate possibilities. The physical world needs engineering context it can trust.
METOMOS develops the connected, verifiable data layer between design intent and physical execution. We do not claim to build the robot, the foundation model or AGI itself.
Why construction is different
Factories repeat. Construction does not.
A manufacturing line gains reliability from repetition. A construction project changes with its site, structure, materials, regulations, design decisions, work sequence and every approved revision.
Automation therefore needs more than recognition. It needs the current engineering meaning of each object and change.
The operational question
What does a robot trust when it moves?
Which approved version is current?
What is this object and what constrains it?
What changed and which outputs are affected?
A plausible shape is not enough. Physical action needs a traceable project state that can be checked before it is used.
Different jobs, one accountable flow
Generative AI proposes. Engineering still has to prove.
02
Symbolic AI makes context explicit
It represents what an object means, how it relates to other objects and which engineering constraints must remain visible and inspectable.
03
Deterministic software calculates
Quantities, costs and affected project states are calculated from controlled inputs so the same conditions produce reproducible results.
04
Humans verify what requires judgment
Trained Metomers review ambiguity, exceptions and delivery standards. Human Verification is a quality boundary, not hidden manual labor.
A disciplined path forward
Construction was never the destination. It was the hardest training ground.
Now
Verified engineering production
METOMOS connects BIM, quantities, costs and schedule context into traceable deliverables for defined project scopes.
Extending
Machine-usable project context
The Foundry is being extended so verified object identity, relationships, constraints, versions and sources can support digital twins, simulation and AI agents.
Future direction
Engineering context for Physical AI
Robots and more capable AI systems will need reliable project state before they can plan or act safely in changing physical environments.
The bridge matters—even if AGI eventually crosses it alone.
More capable AI may eventually perform much of today’s integration work. That possibility should make the claim more precise, not less useful: AI still needs domain context, trustworthy state and ways to verify consequences in the physical world.
METOMOS is building that engineering bridge now: useful to people today and progressively usable by machines tomorrow.
Build from verified context