The challenge
Data is available. Decisions are missing.
Many industrial companies already collect machine, energy and process data. What is often missing is a data basis that can be trusted when taking operational action.
- Data is held in separate systems, files or historian databases.
- Asset, process and energy context is missing or incomplete.
- Dashboards show metrics, but no clear course of action.
- Correlations become visible, but the technical causes remain uncertain.
- It is unclear which action will deliver which energy or economic impact.
Greenformance closes the gap between available industrial data and reliable decisions. The decision layer provides people and AI agents with relevant engineering context, transparent assessment, visible uncertainty and a specific recommended action.
Free data check
How suitable is your machine dataset for the next analysis?
Select a CSV export from a machine, PLC, BMS, SCADA, EMS, historian or energy meter. The Greenformance data check highlights quality issues and statistical patterns and provides an initial reproducible assessment. You can then request an in-depth analysis by Greenformance for the engineering interpretation.
- Free automated initial assessment
- Reproducible evaluation without generative AI
- Initial file inspection locally in the browser
Please use only synthetic or non-critical data that you have anonymized.
Interactive demo
Results depend on data quality
Train an artificial intelligence model (neural network) and experience the impact of data quality.
Same model. Different data basis. Completely different result.
Many AI projects fail not because of the model, but because of the data basis. The Greenformance Data Quality Lab demonstrates interactively why industrial data must first be cleaned, contextualized and turned into a trusted basis for decisions.
Raw data
Available data is not yet decision-ready data. Missing values, noise and absent asset context lead to unstable results.
Cleaned data
Data cleaning improves model quality, but it cannot replace industrial context or technical plausibility checks.
Trusted data
Only context, quality logic and technical plausibility turn industrial data into a reliable basis for decisions by people and artificial intelligence.
Products & Services
Products and services
Three coordinated products connect the analysis of existing data with the use of recommendations in live operations and integration into existing systems.
Greenformance Decision Studio
Assess industrial data and develop decision models.
- systematically assess data quality and potential
- develop, validate and simulate models
- prepare a basis for decisions by specialists and AI agents
- run in the Greenformance Cloud or on a local server
Greenformance Runtime
Use validated models and recommendations in live operations.
- detect inefficient and unusual states
- support operations and maintenance with transparent recommendations
- automate defined optimizations with appropriate safeguards
- run in the Greenformance Cloud, on a local server or an edge device
Greenformance Physics Core
Integrate industrial decision capabilities into existing systems.
- extend existing products with focused capabilities
- reduce integration and development effort
- retain existing user interfaces and system architectures
- for OEMs, system integrators and industrial software providers
Services & pilot projects
Determine the right starting point for your system.
- data and use-case check
- workshops and potential assessment
- root-cause analysis
- jointly defined pilot project
Would you like to explore Greenformance with your own use case? We will identify a suitable path – from the free data check and a product demo to a jointly defined pilot project.
HOW GREENFORMANCE WORKS
From dashboard to decision
Classic dashboards show deviations. Greenformance turns them into assessed recommendations for action.
CLASSIC DASHBOARD
ENERGY COSTS · LAST 24 H
- Reference value
- €1,900
- Status
- Deviation detected
Greenformance adds context, assessment and a specific recommended action to the measured value.
GREENFORMANCE
ILLUSTRATIVE EXAMPLE · DEVIATION ANALYZED
Increased energy consumption due to heat losses
Applications
Typical applications
Energy optimization
Analyze load profiles, operating states and process data to make energy losses and specific savings potential visible.
Anomaly detection
Identify deviations in asset behavior that indicate incorrect operation, wear or unfavorable parameter settings.
Predictive maintenance
Support maintenance teams by identifying critical developments and maintenance needs at an early stage.
Digital twins
Combine domain expertise, process physics and real operating data to explain behavior and assess actions in advance.
Agentic Industrial AI
Greenformance for AI agents
AI agents need more than available data
Greenformance prepares decisions so that engineering context, plausibility, uncertainty, recommendation and expected impact can be considered together.
- analyze relevant asset states more precisely
- prepare technically grounded proposals for operations and maintenance
- access validated information instead of isolated raw data
- operate within defined roles, limits and approvals
The level of automation depends on the use case, technical safeguards and organizational approval. Critical decisions can deliberately remain with people.
Team
The team behind Greenformance
Not every data problem is an AI problem. But effective AI needs a reliable technical data basis.
Greenformance combines industrial experience, physical process understanding and Industrial AI methods.