Good fit
There is visible drag
People repeat the same work every week, or the current stack keeps creating manual follow-up.
Administration and documents
Turn incoming email and documents into a controlled AI workflow
Let AI classify requests, read documents, prepare records, and route exceptions while your team keeps control over approvals and sensitive decisions.
How we make this practical
The goal is not to introduce more tools. The goal is to make one important workflow clearer, faster, and easier to own.
First move
Start with one workflow
We pick a narrow process, define the handoff, and only expand after the team trusts the result.
Guardrail
Keep judgement human
AI can prepare, summarize, route, and suggest. Commercial, legal, and sensitive decisions stay reviewable.
Common bottlenecks
Where administration consumes unnecessary time
Shared inboxes contain requests, invoices, contracts, and questions that must be sorted manually.
People copy information from PDFs and attachments into accounting, CRM, or planning systems.
Approvals are difficult to trace and exceptions remain hidden in long email threads.
Management receives reports late because data first has to be reconciled by hand.
Approach
Automate the routine, expose the exceptions
The strongest workflow does not pretend every document is predictable. It automates high-confidence work and gives uncertain cases a clear review path.
01
Define intake
List channels, document types, required fields, validation rules, and the responsible team for each exception.
02
Build the control flow
Store the original, extract data, validate it, and record what was accepted, rejected, or sent for review.
03
Connect the destination
Send approved data to accounting, CRM, storage, ticketing, or reporting without repeat entry.
Outcomes
Examples of useful automation
- Inbox classification and suggested replies
- Invoice and document extraction with validation
- Approval queues with a complete audit trail
- Automatic updates to CRM, accounting, or dashboards
Related proof
Related guidance and experience
Delivery and ownership
What we arrange before the system becomes business-critical
A working interface is only part of the delivery. We also make clear who owns what, how access is managed, and how the product can continue after launch.
Ownership
Clear agreements about source code, data, accounts, documentation, and the components your organisation controls.
Security
Role-based access, data handling, logging, backups, and a review of the risks that matter for this workflow.
Go-live
Testing with real scenarios, acceptance criteria, migration where needed, and a practical handover to users and administrators.
Continuity
A support route, monitoring where relevant, and a prioritised backlog for maintenance and further development.
FAQ
Can AI approve invoices or contracts by itself?
Only for narrow, low-risk rules agreed in advance. Financial, legal, or unusual exceptions should remain subject to human approval.
Do we need perfect data before starting?
No, but we do need representative examples and clear validation rules. The first phase often exposes which data should be cleaned.
Can we start with one mailbox or document type?
Yes. A focused intake is often the safest way to prove reliability before connecting more teams and systems.