Agencies and solo consultants ship a stream of AI-assisted deliverables: audits, reports, prototypes, landing-page drafts. Revdoku gives that stream a structure — one bucket per client, a protected link per deliverable, and analytics that show engagement.
1. One bucket per client
Create a bucket for each client. Everything the agents produce for that client lands there — drafts stay private, and the bucket becomes the client’s file history.
2. Produce the deliverable — by hand or with any AI tool
Drop the audit, report, or prototype into the client’s bucket — made by hand, exported from your tools, or produced by Claude, ChatGPT, or Codex writing straight into the bucket.
3. Publish it protected
Publish the deliverable folder with a password (and an email requirement if you want a viewer log). Each client gets their own link and password.
4. Watch engagement instead of asking
Analytics show whether the client opened the work, which pages they read, and when — notifications fire on new views, and captured emails identify the viewers.
5. Iterate at the same URL
Revision requests go back to the agent; it updates the bucket and republishes. The client’s link never changes, so there is no version-attachment chaos.
Takeaway
One bucket per client, one protected link per deliverable, analytics instead of “did you see my email?” — that is the whole workflow, and it scales from a solo consultant to an agency team.