Where an AI workflow
makes the most sense

Where it’s not enough to display data or extract a document. An AI workflow helps you understand the context, validate a rule and prepare the next step.

Data Foundation for AI workflows

The data exists, but it’s split across systems, exports, spreadsheets and teams. We map the sources, quality and relationships for reporting, workflows or AI.

AI over BI and reporting

A report shows the change. The workflow explains why, finds the deviation and drafts a comment or recommendation.

Certificate and document control

Data extraction, validation against the standard, flagging exceptions and a structured output for the ERP or operator.

Exception analysis in processes

Finding recurring errors, out-of-spec values and risky states that require intervention or escalation.

Invoice and document data extraction

Extracting headers and line items, matching against the order, validating the data and preparing it for the ERP.

Working with standards and requirements

Finding the relevant sections, comparing them with the documentation and a traceable justification of the result.

QA and compliance workflow

Checking checklists, reports and supplier documents. A clear output: what passed, what’s missing and why.

Also worth mentioning

Internal knowledge workflow

SOPs, directives, rules and past decisions available through answers that come with a source, context and a link to the process.

SOPs, directives and decisions as a traceable answer

The AI returns an answer with a link to a specific directive, rule version or past decision. It’s clear what it’s based on and when the source was last updated.

Where an AI workflowmakes the most sense