From scattered signals to a useful next step.
A software company powered by AI and machine learning. From consulting and data analysis to integration and ongoing maintenance, we connect the work between your systems.
Book a demoThe context travels with the asset.
What was requested, what was built and how it performs belong in one conversation.
- 01
Customer need
Required performance
- 02
Order
Agreed configuration
- 03
Factory
Test & quality evidence
- 04
Delivery
Handover & commissioning
- 05
Monitoring
Condition & service
Data that explains what you are looking at.
A useful data foundation connects signals to the right asset, time and operating condition. We make source quality, missing context and meaningful changes visible so your team can trust what it sees.
- Asset identity, timestamps and data lineage
- Telemetry, weather and maintenance history
- Exceptions with evidence that can be inspected
T-03 · operating context
Illustrative scenarioTemperature follows operating conditions.
The measured temperature stays close to the expected trace at steady load. Keep monitoring the trend.
The change is in the temperature, not the load.
The same load and ambient context now show a divergent temperature trace. Review cooling and maintenance history; this is a prompt for investigation, not a diagnosis.
- Load
- 68%
- Ambient temperature
- 22°C
Intelligence with a reason to be there.
We develop AI and machine learning around a defined operational question: what is changing, what is likely to happen, or which evidence deserves a closer look? The model is one part of the software, alongside data quality and human review.
- Forecasting and anomaly detection
- Inspection assistance and evidence review
- Evaluation and monitoring in the operating context
A forecast is a range, not a promise.
Illustrative scenarioObserved demand, model output and uncertainty should remain visible together. Evaluate a model against the decisions it supports, using agreed test data and operating conditions.
Useful insight should not stop at a dashboard.
Connect an observation to the person, process and system that can act on it. We build operational workflows with clear review steps, permissions and an audit trail.
- Order, production and service exception handling
- CRM, ERP, factory, asset-management and ticketing integration
- Human approval, retries and exception handling
WK-1042 · one connected workflow
Illustrative scenarioA component changes the plan.
The cooling package for order WK-1042 is delayed. Link the supplier update to the purchase order and the affected factory milestone.
Show the dependency, not just the alert.
The factory acceptance test depends on that component. Purchasing and production review alternatives against the customer delivery commitment.
The right people act on the same picture.
Prepare a revised milestone and a customer update for approval. Keep the decision linked to the order and carry the record into delivery and the asset history.
Demonstration only. No order is changed and no message is sent.
Start with one decision. Build for everyday use.
Understand the question
Work with the people closest to the problem. Agree the operating context, the available evidence and what a useful outcome looks like.
Build a focused first version
Connect a representative set of data, make assumptions visible and test the workflow with the team that will use it.
Integrate into the real environment
Fit the software into existing identities, permissions, interfaces and review processes. Make ownership clear before rollout.
Keep it working
Maintain integrations, monitor data and model behaviour, and adapt the software as your operations change.
See where this approach can make a difference.
Explore applicationsYour next advantage
starts with a conversation.
Bring your questions. Let’s explore what comes next.
Book a demo