Teams lose time to repetitive information work
Start with value, not technology
Find where AI can genuinely improve your organisation
We examine processes, systems, information and risks before recommending technology. The result is a practical roadmap rather than a list of fashionable ideas.
Recognisable?
You see potential, but the right starting point is unclear
Data is fragmented across systems and documents
Ideas exist, but business value has not been defined
Privacy and feasibility questions slow decisions
From analysis to daily work
A focused investigation of work, data and value
Part 1
Interview the people who know the process
Part 2
Map systems, information and bottlenecks
Part 3
Assess feasibility, privacy and human control
Part 4
Prioritise opportunities by impact and effort
Practical progress
A roadmap you can make decisions with
- Ranked opportunities
- Clear success criteria
- Key risks and dependencies
- A defined next step
Frequently asked questions
Useful to know before you start
Do we need technical AI knowledge to get started?
No. The scan starts with the work, not the technology. Employees and process owners explain where time is lost, which exceptions they encounter and what information they use. Vinvu translates this with IT into feasible improvement opportunities. Technical knowledge on the client side helps with questions about systems and security, but it is not a prerequisite for the first conversation.
Does an opportunity scan always lead to implementation?
No. A good opportunity scan may also show that AI is not the wisest investment yet. Sometimes a process must first be simplified, information recorded more effectively or a regular system integration implemented. We make those dependencies visible and recommend an appropriate sequence. This prevents an attractive pilot from being built on a process that is not yet sufficiently stable at its core.
Will we receive concrete advice on what to do next?
Yes. The outcome is not a general list of ideas, but a roadmap you can use to make a decision. For each opportunity, we outline the expected value, key dependencies, risks and technical feasibility. For the most promising application, we define a bounded next step with success criteria agreed in advance.
- Prioritised applications and process bottlenecks
- Requirements concerning data, privacy and integrations
- A proposal for a measurable Proof of Value
Who should be involved in the AI opportunity scan?
The best insights emerge when both decision-makers and employees doing the work participate. A process owner can explain objectives and priorities, employees know the exceptions, and IT understands which systems, data and security requirements matter. Not everyone needs to attend every conversation. We agree beforehand who is needed for each topic, keeping the scan thorough without demanding unnecessary time from the organisation.
What information should we have available beforehand?
You do not need to provide a complete technical dossier before we begin. An overview of the relevant processes, applications, information sources and known bottlenecks is usually a useful starting point. During the scan, we determine which additional information is genuinely needed. Sensitive documents or personal data are not collected by default; we first discuss purpose, necessity, access and secure processing.
How are privacy and security addressed during the scan?
Privacy and security are considered while opportunities are prioritised, not only once a solution is being built. We examine which data an application needs, who should have access and where human control must remain. The scan is not a full legal or security audit, but it identifies early which requirements, risks and additional expertise are needed before a Proof of Value can begin responsibly.
A practical first step
Where could this create value in your organisation?
In a virtual introduction, we explore the process, expected value and a responsible first step.
