Reading and sorting
Classifying enquiries, extracting details from routine documents or organising incoming requests.
I help organisations examine repetitive tasks, test practical AI ideas and connect useful automation to the systems people already use.

It is easy to feel overwhelmed by new AI products. A tool may look impressive in a demonstration but still fail to fit your data, approvals or daily work.
I begin with the task: what comes in, what people do with it, which decisions require judgment and what a useful output looks like. Only then do I consider whether AI, ordinary automation or a simpler process change is appropriate.
Classifying enquiries, extracting details from routine documents or organising incoming requests.
Preparing first drafts, meeting summaries or a clear digest from several records, with human checking.
Sending approved information to another system, checking required fields and alerting staff when something needs attention.
Map a repeated process and automate the predictable stages. For example, a submitted form can create a record, notify the right person and prepare a summary without staff copying the same details.
Help staff search approved policies, guides or internal information using everyday questions. Sources, permissions and regular updates matter as much as the chat interface.
Handle common questions, collect initial details and route an enquiry. The system should make it clear when a person needs to take over.
Extract selected information from invoices, applications or structured reports. Results should be checked before they affect payments, eligibility or important records.
Turn existing records into a readable update for managers, highlight missing information or prepare a first draft of a recurring report.
Add a focused assistant, content workflow or document feature to a WordPress website while keeping access and data handling under review.
AI can misunderstand context, produce incorrect information or respond with more confidence than accuracy. A responsible workflow decides what the system may do automatically and where a person must approve the result.
I also review the type of data involved, who should have access, what needs to be logged and how failures will be handled. Not every document should be sent to an outside AI service.
A proof of concept is a small test built to answer a specific question. It may use a limited set of documents or one part of the workflow.
We define the current steps, repeated effort, important exceptions and desired result.
We select one useful scenario and agree how we will judge whether it works well enough.
We look for inaccurate output, missing context, privacy concerns and awkward handovers.
We improve, expand, change direction or stop based on evidence—not excitement alone.
No. Explain the task, the information involved and the result you need. Tool selection comes after the workflow review.
Sometimes several stages can be automated, but exceptions, sensitive decisions and unusual cases often need human judgment. A mixed workflow is usually more responsible.
Yes, in many cases. The documents need to be organised, current and permitted for that use. Access control and source citations may also be required.
No. AI output can be wrong. Testing, clear limits and human review should match the risk of the task.
Often it can, through an application programming interface (API) or webhook. I first check what each platform supports and how errors will be handled.
I can help you decide whether AI, standard automation or a process improvement is the sensible next move.