EVEREDGE
Editorial Workflow Platform for Multi-Volume Document Production
Case study
OtherWeb Application14 weeks

A publishing-adjacent services company handling 500+ DOCX assets per month

OtherWeb Application14 weeks

Editorial ops was running 11 separate tools to move a document from intake to edit to merge to format to export. Turnaround was unpredictable and any one tool outage stalled the whole pipeline.

The challenge

What they came to us with.

Editorial ops was orchestrating 11 separate tools — intake in one system, editing in another, merges in a third, PDF export in a fourth, and a spreadsheet that tied them together. Turnaround was unpredictable and any one tool outage stalled the whole pipeline.

Big volume merges were the worst pain point: synchronous operations against multi-hundred-page DOCX files would OOM and time out unpredictably, and failures were not cleanly recoverable. Editors were keeping manual spreadsheets to track what had and hadn’t gone through.

Our approach

How we built it.

We replaced the 11-tool chain with a single Next.js 16 workspace. Editors drag and reorder document sections with dnd-kit, convert between DOCX, PDF, and HTML (Aspose Words Cloud + docxtemplater + mammoth), collaborate inside resizable side-by-side panels, and operate inside role-gated review flows. Authentication, storage, and access control are Firebase; errors flow to Sentry.

The architectural unlock was moving every document merge onto Google Cloud Tasks with idempotent task IDs. Synchronous merges could not survive large volumes; async made failures recoverable, kept the UX feeling instant, and let us scale heavy operations independently of the request path.

The outcome

What shipped. What changed.

Tools in editorial pipeline

Before: 11After: 1
-91%

Median doc turnaround

Before: 3.5 daysAfter: 10 hours
~8x faster

P99 merge failure rate

Before: 14%After: <1%
-93%

Review cycle method

Before: Email attachmentsAfter: In-app with audit trail
Eliminated

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