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Geminus

Physics-based AI that optimizes complex industrial systems in real time

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DR by Ahrefs
30 no change since last check

Ahrefs Domain Rating benchmarked 26 Oct 2026, rebuilt 26 Oct 2026.

Industrial AI platform that uses physics-based modeling to predict and optimize complex systems in real time, deployed across oil & gas, energy, and defense

What it is

Screenshot of the Geminus homepage
geminus.ai, as visitors see it

Geminus builds physics-native AI that understands, predicts, and optimizes complex industrial systems in real time. The platform combines physics-based simulation with real-world data and historical information, enabling it to reason accurately about conditions never previously observed. Unlike conventional AI that extrapolates from historical patterns, Geminus starts from the physics and first principles of each asset, fusing data from simulators, sensors, and operational context while providing uncertainty-aware recommendations.

The system deploys across entire industrial operations in weeks rather than years, delivering measurable results from day one. It has helped major refiners reduce methane flaring by 25% while increasing production by 5%, and deliver $100M in value in year one. Geminus operates across critical infrastructure including refineries, electric grids, nuclear power, renewable energy, data centers, space systems, and defense programs.

The platform provides dedicated AI agents for every industrial asset, with guard-railed autonomy grounded in physics, multi-fidelity data fusion with real-time feeds, and decision-making with calibrated confidence measures. It includes auditable workflows with complete chain of evidence, cloud-native deployment with on-premises support, and integrations via REST API and OPC UA.

What it is built with

  • Physics-native optimization grounded in system physics
  • Multi-fidelity data fusion with real-time feeds
  • Guard railed autonomy with rigorous framework
  • Decision-making under uncertainty with calibrated confidence measures
  • Systems of surrogates for industrial-scale complex systems
  • Auditable workflows with complete chain of evidence
  • Cloud-native with on-premises support
  • REST API and OPC UA integration
  • SOC 2 Type II certified security
  • Deploys in weeks across entire operations

Pricing

Pricing model: Contact for pricing

Geminus metrics

Benchmarks for geminus.ai: Ahrefs Domain Rating and Majestic link data, with the change since the last build.
MetricValue
Domain Rating30 no change since last check
Trust Flow18 no change since last check
Citation Flow30 no change since last check
Referring domains141 no change since last check
External backlinks632 no change since last check

Ahrefs Domain Rating benchmarked 26 Oct 2026, rebuilt 26 Oct 2026. Main build topic: Reference/Education (18). Majestic benchmarked 26 Oct 2026, rebuilt 26 Oct 2026. Link data built by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.

Geminus domain build sheet

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Public RDAP record, last read 26 Oct 2026, 18:50 UTC.
Domain age8 years
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RegistrarEuroDNS S.A.
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Questions from the bench

How quickly does Geminus deploy?
Geminus deploys across entire systems in weeks, not months or years. The company helped a major refiner move from pilot to production in days, and delivers measurable operational gains from day one.
How is Geminus different from other industrial AI?
Geminus uses physics-based reasoning instead of pattern-matching on historical data. It understands the underlying physics of each asset, fuses multiple data sources, and provides uncertainty-aware recommendations with complete chain of evidence that operators can audit and trust.
Where can Geminus be deployed?
Geminus is cloud-native and runs in a dedicated instance in the Geminus Cloud or in customer environments on Azure, AWS, or GCP. On-premises deployments are supported via OpenShift. Trained models are exportable for independent operation in any location.

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