FactVerse Platform
DataMesh connects live data, spatial twins, and AI reasoning in one platform so operations teams can simulate, validate, and execute with confidence.
Data Fusion Services brings operational data into one decision layer.
FactVerse Twin Engine validates actions against space, process, and equipment logic.
FactVerse AI Agent turns signals into recommendations, simulations, and next-best actions.
Executable Twin
A visualization twin helps teams see assets and spaces. An executable twin connects geometry, live data, operating rules, simulation, and work orders so decisions can be tested, approved, and carried into field execution.
See
Show asset location, status, and spatial context so teams share the same operating picture.
Test
Run scenario checks, AI recommendations, and workflow logic against the current state of the site.
Act
Send approved actions into Inspector, Checklist, Simulator, or enterprise systems with traceable records.
Physical AI, world models, and embodied intelligence need to understand how a real factory operates. Visual appearance and dashboard signals are only the entry point; AI and robots also need asset semantics, spatial relationships, process steps, equipment state, safety boundaries, work-order history, and simulation results. An executable digital twin organizes that context into a computable, verifiable, and traceable site model, so the factory brain can use real operating constraints when recommending actions, training robots, or testing scenarios instead of judging only from images and dashboards.
Industrial physics in action
A digital twin becomes more valuable when teams can compare how air, heat, gases, networks, equipment, and robots may behave before committing a change in the real environment.
Project-enabled analysis starts with a bounded decision, representative geometry and data, an agreed evidence level, and responsible engineering review.
See where rack-level thermal margin may be narrowing. Compare cooling degradation, load growth, and layout options before adding capacity or changing the room.
Decision evidence: Rack-inlet conditions, thermal margin, scenario comparison, assumptions, and reviewable findings
Explore data center operationsCompare airflow, gas dispersion, exhaust capture, and detector coverage across normal and degraded HVAC states before installation or safety changes.
Decision evidence: Affected zones, capture behavior, detection coverage, model assumptions, and confidence
Explore semiconductor operationsConnect live network context with forecasting and hydraulic or thermal analysis to prepare for imbalance, cold weather, preheating, and resilience scenarios.
Decision evidence: Measured-data calibration, network comparisons, operating limits, and auditable decisions
Explore Smart District HeatingUse Designer to create reusable scenes, then take selected questions into airflow, rigid-body, Isaac, PhysX, or Newton workflows when deeper validation is needed.
Decision evidence: Scenario variants, decision metrics, runtime evidence, and reusable SimReady context
Explore process simulationDataMesh connects operational data, executable digital twins, simulation, AI decision intelligence, and frontline workflows so industrial teams can validate decisions before acting in the real world.
Trusted By Industry Leaders
Stay up to date with product releases, customer stories, and partnership announcements from DataMesh.
Explore how the latest FactVerse updates help teams work more efficiently in real-world industrial scenarios. From clearer site visibility to easier simulation setup and content sharing, these improvements deliver a smoother experience across key industrial workflows.
Faurecia's Yancheng plant uses DataMesh Director to bring XR training into critical frontline skills training, helping teams practice standardized procedures, reduce equipment occupation and safety risk, and turn training records into a repeatable capability.
DataMesh has joined the Alliance for OpenUSD to help advance industrial OpenUSD semantics and SimReady Asset development for digital twins, simulation, Physical AI, robotics, and AI Agent workflows.