Less manual work, with targeted AI support.
We start from your daily work: we look for the steps where AI can help to process data, find information or prepare case handling. For the chosen task we build a solution that fits both the programs you already use and the work of your team.
First we try the solution on your own samples to see how it works, where it makes mistakes and how much checking it needs. We review these results and the expected running cost together before deciding on rollout.
Which tasks are worth examining?
The examples are possible custom solutions, not ready-made product features or references.
Processing documents
We pass on the data extracted from documents in an orderly form for further work, with a human check.
Sorting incoming requests
By grouping and summarising emails and tickets, we help your team see sooner what needs to be done.
Searching internal information
We help you find the information you need in the internal documents available to you, and show the sources behind each answer.
Preparing case handling
We build a solution that drafts replies and suggests tasks, so your team has more time to check and decide.
We start with one chosen process.
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We understand the current work.
We review the steps, the systems in use, the data, and where unnecessary manual work arises.
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We agree what counts as a good result.
We agree the expected quality, the checking needed and an acceptable range for the running cost.
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We try it on your own samples.
In a scoped test we examine the usable results, the faulty cases and the human intervention needed.
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We plan the rollout.
Based on the results, we decide on integration, access, logging and ongoing operation.
We measure the usable result.
Depending on the task, we look at lead time, the corrections needed, the time spent on human checks and the cost per processed item. We compare the results with the original process.
The solution stays verifiable.
We define in advance which data the solution may process, who can access its results and which steps need human approval. How uncertain or faulty cases are handled is designed as part of the process.
When is a simpler solution the better choice?
If clear rules or a direct connection between systems can solve the task more reliably, that is what we recommend. We choose the technology based on the task, the quality of the data and the running cost.
A concrete example: rovatix
rovatix extracts data from documents, which the user can check and correct. The expected output can be fitted to the next step of the workflow or to the program in use.
Which repetitive task should we look at?
Briefly describe where the process starts, what its result should be and where manual work is needed today. Based on that, we suggest a first step.