Energy company
Read the use case Automated checks of partner invoices
Every partner invoice is checked against the agreed rates, fees and rebates. Rule-based, fully separate from SAP, and tested on historical invoices.
Home / AI Agents
Let AI handle the repetitive work
Checking invoices, opening case files, sorting requests, preparing reports. A lot of work follows the same steps every time. We build AI agents and automations that take over that work, so your people have time for what really matters.
- Start
- Proof of concept in 3–4 weeks
- Input
- Your own documents, data and one expert from your team
- Safety
- Isolated from your production systems
- Outcome
- Working proof of concept, tested on historical data
- After that
- Pilot, integration and user training
Examples
What an AI agent can do for you
Invoice checks
Automatically check partner invoices against agreed rates, discounts and fees. Variances surface straight away.
Opening case files
Collect data in a structured way, check that it’s complete and prepare the file.
Sorting emails and requests
Read incoming questions, classify them and route them to the right person or system.
Checks and matching
Recognise names, variants and spellings, for example in customer data or supplier lists.
Knowledge assistant
Find answers in procedures, contracts and internal documents, with a reference to the source.
Reporting
Gather figures, summarise them and prepare a first draft of the report.
Our approach
AI where it helps, fixed rules where it must
Not every problem needs AI. When the rules are fixed, as with invoices against contract terms, we build a fully predictable, rule-based solution. We use AI where language, documents or variation come into play. You get reliable results and stay in control.
Rule-based
Calculations, checks and fixed steps. Every result can be explained.
AI-driven
Reading, summarising, classifying and recognising variants. A person decides.
How a proof of concept runs
From idea to evidence in four steps
- 01
Pick the use case
Together we choose one process with clear value and available data.
- 02
Rules and test cases
We capture the logic and you confirm a set of reference cases.
- 03
Build
We build the proof of concept, safely isolated from your production systems.
- 04
Test on real data
We run historical cases, measure the results and advise on the next step.
A proof of concept delivers evidence. Does it work reliably, and is the value big enough to scale up? You get a working solution, documented logic, test results on historical data and advice for a pilot or production.
Use case