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AI use cases

Document to reviewed record

For: Procurement, finance, trading and logistics teams handling supplier, shipping and customs paperwork

What happens today

Documents arrive in mixed formats and someone re-types the important fields into a system.

What changes

Agreed fields are extracted, validation rules are applied, and the record is prepared for export to accounting, ERP or a tracking sheet.

What a person still reviews

Uncertain fields are flagged and routed to a reviewer. During a first pilot the export itself waits for a person; automatic export only if later agreed in scope.

How a pilot measures it

Field accuracy, review time per document and the exception rate, against a baseline.

Related service

AI applications & agents.

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Enquiry triage and drafted replies

For: Sales, support and admissions teams answering the same questions by email and WhatsApp

What happens today

Every message is read, classified and answered by hand. Urgent ones wait behind routine ones.

What changes

Incoming messages are classified, the useful fields are extracted into the CRM or sheet, and a reply is drafted from your own material.

What a person still reviews

A person edits and sends every reply. Anything unclear goes to a queue with the reason shown.

How a pilot measures it

Response time, correction rate on drafts, and the share of messages that needed a person.

Related service

Workflow automation.

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Question to supported answer

For: Operations, HR and compliance teams whose knowledge lives in policies, manuals and past cases

What happens today

Staff search shared drives or ask a colleague. Answers vary and the source is rarely checked.

What changes

An assistant answers from approved documents, shows the sources it used and respects who is allowed to see what.

What a person still reviews

Questions the sources cannot support are declined and routed to a person. The evaluation reports how often that happened.

How a pilot measures it

Correctness on an agreed evaluation set, source relevance and the rate of unanswerable questions.

Related service

AI applications & agents.

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Operations that live in spreadsheets

For: Distributors, traders, service businesses and admin teams running orders, bookings or accounts in spreadsheets

What happens today

Emails, messages and invoices are read and typed into the sheet. Follow-ups depend on someone remembering.

What changes

A layer reads what comes in, prepares the entry for the sheet or the billing tool, and prepares reminders when a row goes stale. The spreadsheet stays where the scope allows.

What a person still reviews

Which entries a person approves is agreed before the pilot starts. Uncertain entries wait in a review tab; every automatic write, if any are agreed, is logged.

How a pilot measures it

Handling time per item, correction rate and unresolved items, before and after.

Related service

Spreadsheet-driven businesses.

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Periodic reporting to funders and boards

For: Mission-led organisations, programme teams and small finance functions reporting to several audiences in several formats

What happens today

Each report is assembled by hand from the same underlying records, in a different template every time.

What changes

Reports are assembled from the records you already keep, in each audience’s format, with the numbers traceable to their source.

What a person still reviews

A person approves the final version. Anything the records cannot support is marked, not filled in.

How a pilot measures it

Hours per reporting cycle, corrections after review and time from period end to submission.

Related service

Non-profits.

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Approval defaults are the same in every example: during a first pilot, consequential actions such as sending a message or writing to a business record wait for a person to approve them. After the evaluation, automatic actions can be agreed per action, with validation rules, logging and exception handling written into the scope.