AI app for finance · no coding needed
Subscription contract revenue leakage lab
Detect contractual billing omissions and overcharges.
Made for: Recurring-service businesses
What it does for you
The problem
Renewal prices and approved increases are not reflected in billing.
What it gives you
Finance-reviewed pricing exception queue
What you give it
Authorized contract termsinvoice histories
How it works, step by step
- Match effective price periods
- Compare billed amounts
- Assemble correction evidence
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned finance-reviewed pricing exception queue with source references and unresolved questions
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 Subscription contract revenue leakage lab 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 Subscription contract revenue leakage lab 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 build3 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare27 KB
- prompt-vps.mdThe same build on your own server (Docker)27 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria15 KB
- demo/index.htmlThe working demo on sample data196 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
Detect contractual billing omissions and overcharges
Confirm the buyer's problem and scope, collect authorized contract terms and invoice histories, then follow this sequence: 1. Match effective price periods. 2. Compare billed amounts. 3. Assemble correction evidence. Resolve uncertain cases with qualified reviewers, approve finance-reviewed pricing exception queue, and measure net correctable revenue minus remediation and review cost against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One contract family; human interpretation and customer communication required. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Reconcile calculations to approved records. Keep proposed entries and payment actions under finance-team control. Never invent missing financial inputs. One contract family; human interpretation and customer communication required. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One contract family; human interpretation and customer communication required. Implement one approved input format, a bounded representative case set and the first two task modules: match effective price periods; compare billed amounts. Support the third module with operator review: assemble correction evidence. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Accounting exports, invoice records and finance review processes. Source repositories, task trackers and report exports. Keep findings as review proposals until authorized owners accept the resulting actions. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Submission and rules, Evidence-linked exceptions, Reviewer decisions and export. Open on a review queue ordered by reviewer-selected priorities. Show each finding beside the original evidence and applicable rule. Provide accept, dismiss and needs-information controls with reasons. A separate report view summarizes confirmed findings and unresolved items, not raw AI flags. Make the task-specific outcome finance-reviewed pricing exception queue visible beside its evidence, review state and value baseline.
