How we use AI in projects
We start with a repeated task or a decision that takes too much time. We define data, boundaries and human review before connecting an AI model to a workflow.
Content published by Midavco · VEVEN SOFTWARE SRL
1. Choose a use case
We identify a task with enough volume and a verifiable outcome: sorting enquiries, extracting document information or searching internal knowledge. We do not promise full automation before reviewing the data.
2. Design the workflow and controls
A form can send an enquiry for classification, then to the CRM and the responsible person. A document can pass through extraction, human review and approval. For customer answers we define sources, allowed responses and human handoff.
- Enquiries: classify → review → route
- Documents: extract → review → approve
- Support: retrieve sources → suggest answer → escalate
3. Protect data and test
We agree which data can be processed, who may access it and how long it is retained. We test real examples, wrong answers and cases where the model must stop. Integrations, providers and compliance requirements are approved per project.
Sources
4. Measure before expanding
We compare processing time, correction rate and adoption with the starting point. If the workflow helps and is sufficiently reliable, we expand it. Otherwise, we revise the data, rules or approach.
Have a time-consuming process?
We can determine whether AI, simple automation or a process change makes more sense.