Name and logo are withheld under NDA. This was a client engagement, not a concept project.
Starting problem
What was taking too long.
Operations staff read incoming documents, copied fields into spreadsheets, and decided who should handle each request. Review was slow and intake quality varied.
Our work
What the team delivered.
We added document upload, classification, field extraction, and a reviewer queue. A person still approved anything before it was acted on. The team was one project lead, two developers, and a designer.
Outcome
What the client reported.
The client reported that repetitive reading dropped and briefs arrived more complete. That feedback came from the review after the 8–12 week engagement. We are not publishing a time-saved figure because one was not agreed for public use.
Visual evidence
A labelled demonstration.
The client has not approved a screenshot of their live system. The picture below is a demonstration of the kind of screen we built. It is not their interface and it does not show their data.
Demonstration — not a client screenshot
AI Document Workflow Automation
B2B Services · 8-12 weeks
Document upload
AI classification
Field extraction
Reviewer queue
Delivery
Features and how the pieces fit.
Features
Document upload
AI classification
Field extraction
Reviewer queue
Audit-friendly history
Architecture
Upload portal
AI classification service
Review dashboard
MySQL records
Email notifications
Before
Manual document reading
Copy-paste into spreadsheets
Slow handoffs
Inconsistent intake quality
The AI workflow did not replace our team. It removed the repetitive reading so people could make decisions faster.
A mid-sized B2B operations team Quote from the project record. The speaker’s name is not published under the NDA.
A similar problem?
Tell us what is slow in your team today.
We will say whether a first version like this fits, and what we would need from you.
