PDF Vector + Postgres: searchable paper takeaways
Turn research PDFs into structured takeaways with PDF Vector and Postgres. No more scattered notes…
Automate document-heavy operationsβintake, approvals, contracts, and handoffsβso files land in the right place, teams get notified, and nothing stalls in email threads.
You connect the tools you already use (like Gmail, Google Drive, Slack, and Google Sheets) and let a workflow handle the busywork. A trigger starts itβan n8n Form submission, a new email, or a file upload. Then actions run in order: extract details, create a document, request approval, and store the final version. Many workflows add AI steps to summarize content or pull fields from attachments. Honestly, itβs like giving your process a reliable checklist that runs itself.
Usually, no. Most Flowpast workflows are plug-and-play: you connect accounts, paste a template, and choose where files should go.
It depends on your volume, but the biggest wins come from eliminating repeated steps. If you spend about 2 hours a day renaming files, copying data into Sheets, nudging approvers, and hunting for the latest version, automation can cut this in half quickly. Teams also avoid rework because fields are captured once and reused across docs, emails, and logs. The result is faster approvals, fewer mistakes, and more time for client work instead of admin.
Youβll need an n8n instance (cloud or self-hosted) and access to the apps youβre connecting, like Google Workspace or Slack. Plan to create API credentials or OAuth connections for each integration, then test with a sample request. If you want AI steps, bring an OpenAI or Google Gemini key (or use OpenRouter) and decide what data youβre comfortable sending for processing. Start small: one intake β one document β one approval path, then expand.
Turn research PDFs into structured takeaways with PDF Vector and Postgres. No more scattered notes…
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