Capabilities
Software & AI
Software that runs real operations, and AI where it actually improves a decision.
The background is a map of DNT's six areas and the connections between them. Digital Products is connected to Software & AI. Software & AI is connected to Digital Products, Connected Systems, Automation & CTS and R&D. Connected Systems is connected to Software & AI, Automation & CTS and Hardware & Machines. Automation & CTS is connected to Software & AI, Connected Systems and Hardware & Machines. Hardware & Machines is connected to Connected Systems, Automation & CTS and R&D. R&D is connected to Software & AI and Hardware & Machines. This page belongs to Software & AI.
The problem
When systems don't talk to each other
Data sits in separate systems, people copy numbers between screens, and decisions wait for someone to put the pieces together. Adding another tool rarely helps.
At a glance
Overview
We build the software layer that connects machines, data and people: platforms, integrations, data flows and the interfaces people work in. Where it adds real value, we add AI - to classify, predict or assist - and we keep it explainable and under control.
We build new systems and develop existing ones further.
Where it fits
Software & AI is usually the layer that holds the other areas together: it reads data from automation and devices, makes it useful, and sends decisions back.
Software & AI
What we build
Platforms
Web and backend platforms that carry the daily operation.
AI Systems
Models and AI functions where they improve a decision or a task.
Automation
Software that takes over repetitive steps and routine decisions.
Data
Collection, storage and processing of data from systems and devices.
Interfaces
Dashboards and tools that people can actually work in.
APIs
Integrations that let systems exchange data reliably.
Systems
Typical system combinations
- Sensors
- Data platform
- Dashboard
- Existing systems
- API integration
- Shared data model
- Reports
- Machine data
- AI model
- Suggestion to the operator
Illustrative example
Honestly
Is it the right choice?
A good fit when
- Data exists but is not used
- Several systems need to work as one
- Manual steps repeat every day
Probably not the right choice when
- A standard product already solves the problem well
- There is no data to build AI on
- The goal is AI for its own sake
Technical view
We design the data model and the interfaces first, so the systems underneath can change without breaking what people use. AI functions are built with clear inputs, logged decisions and a way for a person to override them.
- APIs and integrations
- Data models and storage
- Web interfaces and dashboards
- AI functions with logging