The starting point
Review work took days and volume was difficult to audit. Work crossed documents and inboxes rather than living in one queue. That made the operating process itself a useful place to focus the software effort.
The client remains anonymous under NDA. The review criteria, records being processed and internal systems remain confidential.
The delivered application
The replacement was a queue-driven web application built with Laravel, Postgres and React, hosted on DigitalOcean. The engagement comprised a 14-week build followed by an ongoing retainer.
The important architectural shape is the queue: review work has an explicit place in the application rather than being represented only by scattered messages. A queue makes it possible to reason about waiting work and the operating process together.
The reported outcome
The reported outcome was a reduction in median turnaround from days to under thirty minutes, approximately 95% cycle-time reduction, and auditable volume for the first time.
These reported figures are specific to the engagement; a sample size and observation window are not available publicly. A different workflow needs its own baseline and measurement.
What another team can take from it
Before choosing an automation tool, map the inputs, handoffs, decisions and exception paths in the current process. As an illustrative exercise, separate the time someone spends reviewing an item from the time it waits for an owner. A faster interface will not necessarily fix an unclear handoff.
This case is conventional workflow automation. Where decisions can be expressed as rules, a conventional application may be enough; uncertain text interpretation is a separate question to test.
Discuss your workflow
Bring a short description of the process and where work stalls. We can explore whether you need a focused system review, a product build or an AI adoption roadmap. Detailed reference discussions remain subject to confidentiality after an introductory call.