AI Document Intake Workflow

Challenge

The team received a steady stream of documents that needed classification, data extraction, and review before staff could begin client work. The manual process was slow, inconsistent, and difficult to audit because each reviewer used a slightly different checklist. The client wanted to use AI to accelerate intake, but only if the workflow preserved human review and made exceptions visible. The challenge was to design automation that supported judgment rather than hiding risk behind a black box.

Approach

Solution

The workflow ingests incoming documents, extracts relevant details, and presents the structured output in a review queue. Staff can accept, adjust, or escalate each item, while the system preserves the original source context for auditability. Exceptions are surfaced as work items rather than buried in logs, and repeated review decisions can inform future improvement. The result is a practical AI workflow that reduces repetitive intake effort while keeping accountability with the people responsible for final decisions.