AI app for sales · no coding needed
Deal review briefing
Deal narratives separate verified buyer evidence from seller assumptions.
Made for: Sales managers running weekly pipeline reviews
What it does for you
The problem
Opportunity updates hide missing buyer evidence and commitments.
What it gives you
Deal review and next-step brief
What you give it
Confirmed CRM recordsauthorized sales activity
How it works, step by step
- Summarize stated needs
- Extract confirmed commitments
- Flag missing stakeholders
- Distinguish assumptions
- Highlight stalled steps
- Prepare manager questions
What you see on screen
- Deal overview
- evidence gaps
- next actions
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 Deal review briefing 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 Deal review briefing 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 Cloudflare22 KB
- prompt-vps.mdThe same build on your own server (Docker)22 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data195 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 sales managers running weekly pipeline reviews, turn confirmed CRM records and authorized sales activity into deal review and next-step brief. Address the recurring problem: opportunity updates hide missing buyer evidence and commitments. The pilot measures useful actions and unsupported forecast assumptions against the buyer's current method, before the larger build.
Agree definitions, import authorized data, validate coverage and identifiers, compute transparent measures, group relevant evidence, review findings, assign investigations or improvements, and repeat on a comparable period. Start with confirmed CRM records and authorized sales activity and finish with deal review and next-step brief.
How the AI works
Classify text, summarize evidence and propose explanations to investigate. Compute financial or operational measures with deterministic code. Separate observed patterns from causal claims and preserve examples that contradict the summary.
Safeguards
Keep product capabilities and commercial terms verified. Use authorized customer records and require review before outreach, promises or pricing exceptions. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.
What to build first
Begin with sales managers running weekly pipeline reviews and one recurring use case. Build the first two modules: summarize stated needs; extract confirmed commitments. Provide operator assistance for the third module: flag missing stakeholders. Deliver deal review and next-step brief through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.
What it can connect to
Approved sales collateral, CRM records and product or pricing information. Read-only business data exports, reporting databases and task trackers. Reconcile source totals before scheduling recurring data refreshes. These are candidate integration categories, not verified supported connectors.
The screens in detail
Open with a compact overview and filters for the relevant period or segment. Let users drill from each theme or metric into underlying records. Keep source definitions and missing-data notes near the result. Use an action panel to assign investigations and record what was learned. In this product, the first view is deal overview, followed by evidence gaps and next actions.
