AI-assisted workflows
Automation first. AI where it adds value.
Not every process needs AI. Use predictable rules for predictable work, and consider AI when text or other unstructured inputs make those rules difficult to maintain.
Discuss your process ↗When this is a good fit
For a clearly defined task such as classifying incoming text or extracting fields from varied documents, where a person can review uncertain results before they enter the business process.
Typical AI-assisted workflow use cases
- Classifying incoming requests or free-text inputs
- Extracting structured fields from documents
- Categorizing comments, descriptions or tickets
- Routing information based on content
- Summarizing text into a defined reporting structure
- Handling unstructured inputs before they enter an existing reporting process
What the work includes
A practical scope, built around your process.
- 01
Define one bounded task, representative inputs and acceptance criteria.
- 02
Assess whether conventional automation is enough before introducing an AI step.
- 03
Explore a controlled workflow with human review, exception handling and agreed data-access boundaries.
What this could look like
An illustrative workflow
An illustrative workflow proposes categories for free-text requests and routes uncertain suggestions to a reviewer. Approved categories feed the existing reporting process; the AI output is not treated as a verified fact.
- Incoming text / documents
- Rules where possible
- AI classification / extraction
- Review uncertain results
- Approved output enters workflow
What you take forward
An agreed workflow design and, where suitable, a scoped pilot with documented review criteria. Feasibility, provider choice, costs and data handling are assessed before implementation; newer AI capabilities are approached incrementally.
Start with your process
Which process would you like to simplify?
Tell Ralmay about a recurring report or manual process. Start with what happens today and where the work gets stuck.