AI app for customer support · no coding needed
Support attachment redaction station
Reviewable screenshot sanitization before tickets leave the team.
Made for: B2B support operations teams

What it does for you
The problem
Sensitive information remains embedded in shared screenshots.
What it gives you
Approved sanitized attachment pack
What you give it
Authorized screenshotsredaction policies
How it works, step by step
- Detect candidate identifiers
- Mark sensitive regions
- Suggest redactions
- Preserve originals securely
- Require reviewer approval
- Export sanitized copies
What you see on screen
- Upload tray
- Redaction preview
- Release log
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Support attachment redaction station with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Support attachment redaction station with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links1 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare23 KB
- prompt-vps.mdThe same build on your own server (Docker)23 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data200 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
For b2B support operations teams, turn authorized screenshots and redaction policies into approved sanitized attachment pack. Address this specific problem: sensitive information remains embedded in shared screenshots. The aim: reviewable screenshot sanitization before tickets leave the team. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.
The buyer creates a project, supplies authorized screenshots and redaction policies, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final approved sanitized attachment pack before use. Retain source links and a version history for the next cycle.
How the AI works
Detect candidate sensitive text with human confirmation. Keep model suggestions separate from verified facts. Link factual outputs to authorized input evidence and show missing information explicitly. Use deterministic checks for counts, dates, identifiers and arithmetic where applicable. A designated reviewer validates consequential outputs and signs off the delivered result.
Safeguards
Keep customer account access scoped. Escalate missing evidence and consequential exceptions to staff. Review quality alongside any speed measure. Images only; no automated deletion of originals. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.
What to build first
Costed pilot: Images only; no automated deletion of originals. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: detect candidate identifiers; mark sensitive regions. Support the third task through an assisted review queue: suggest redactions. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of approved sanitized attachment pack. Authentication, account isolation, deletion controls and basic operational logging are included. Specialized production certification, live write integrations and broader rollout are not included unless explicitly stated.
What it can connect to
Support inboxes, help centers, order records and customer feedback systems. Approved repositories, application APIs, execution platforms and monitoring systems. Validate current API access and behavior during discovery before promising compatibility. Begin with uploads and exports of authorized screenshots and redaction policies. Any named system or connector is a candidate requiring current access and compatibility checks; no live connection is included by default.
The screens in detail
Show a work backlog, proposed changes and verification results. Link each item to its source configuration, code or data mapping. Provide execution logs and an owner-facing health view. Keep environments and approval states clearly separated so a draft cannot be mistaken for a live change. Open with upload tray; move into redaction preview for the detailed task; finish in release log for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.





