Document extraction for field operations
PDFs and email attachments become structured operating records with review queues.
Case note
The implementation was treated as a small operating system: visibility first, ownership next, automation only after the workflow was clear.
The starting point
Operational documents arrived as PDFs and email attachments. Staff manually copied client name, location, due date, service type and notes into a tracker.
The important signal was not that the team was working badly. The issue was that work depended on memory, copied data, parallel system checks and priority decisions without a shared source of truth. The first value was turning invisible work into a visible workflow.
The implementation
Ductio created a document intake workflow that extracts required fields, marks confidence, sends low-confidence items to review and updates the operating tracker.
The scope stayed deliberately small. Rules cover repeatable work, AI summarizes or classifies where free text adds context, and sensitive decisions remain in human review. AI as support inside the process, not as autopilot.
What was used
Tooling was chosen from the process outward, not from a pre-decided technical preference. Each piece needed a clear owner, a stable integration path and a simple way to inspect errors.
In practice, the build combined Inbox, Drive/SharePoint, OCR, AI extraction, Supabase, Dashboard. The tools visible to the team stayed close to their daily work, while integration logic was documented and kept separate from sensitive commercial decisions.
The improvement showed up in daily work.
Rather than treating the result as a dashboard, the team felt it in three specific moments: less manual preparation, less context hunting, and fewer doubts about who needed to act.
Copy-paste: Manual field transfer moved from High to Low.
Review focus: Items needing human check moved from All docs to Exceptions.
Tracker quality: Structured records completed moved from Patchy to Clean.
What changed after launch
The team kept human control over uncertain fields while removing most repetitive data entry.
The most valuable change was operational calm. The team stopped chasing fragments and started working from a shared sequence: intake, context, decision, action and evidence. 75% less copy-paste
The workflow in one line
How it was built
Attachments are stored, parsed through OCR/extraction, transformed into normalized fields and routed by confidence threshold before being written to the tracker.
The stack was pragmatic: Inbox, Drive/SharePoint, OCR, AI extraction, Supabase, Dashboard. Tools were chosen for ownership, integration and maintainability, not for theater. The result is a system the team can understand and operate.
What was delivered
- Inbox intake
- PDF extraction
- Confidence score
- Review queue
- Tracker update
- Manual data entry dropped sharply for repeated service documents.
- Low-confidence fields stayed visible for human review.
- Operations gained a cleaner weekly view of pending work.
