AI app for executives and strategy · no coding needed
Post-merger operating model mapper
Map operating differences before committing integration work.
Made for: Acquisition integration leaders

What it does for you
The problem
Integration plans overlook incompatible processes and responsibilities.
What it gives you
Integration operating-model comparison
What you give it
Approved organization chartsprocess inventories
How it works, step by step
- Align business functions
- Compare decision rights
- Identify duplicate handoffs
- Surface process conflicts
- Record integration choices
- Export workstream charters
What you see on screen
- Entity map
- Operating differences
- Integration choices
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 Post-merger operating model mapper 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 Post-merger operating model mapper 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 Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 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
For acquisition integration leaders, turn approved organization charts and process inventories into integration operating-model comparison. Address this specific problem: integration plans overlook incompatible processes and responsibilities. The aim: map operating differences before committing integration work. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.
The buyer creates a project, supplies approved organization charts and process inventories, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final integration operating-model comparison before use. Retain source links and a version history for the next cycle.
How the AI works
Propose function mappings for leadership 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
Show source dates and distinguish evidence from strategic assumptions. Keep sensitive company plans restricted to authorized participants. Two functions; employment and transaction decisions excluded. 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: Two functions; employment and transaction decisions excluded. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: align business functions; compare decision rights. Support the third task through an assisted review queue: identify duplicate handoffs. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of integration operating-model comparison. 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
Internal reports, public company information and decision registers. Read-only operational exports, calendars and finance or inventory records as relevant. Start with plan exports and retain human approval for execution. Begin with uploads and exports of approved organization charts and process inventories. 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
Place editable drivers and constraints beside a clearly labeled scenario output. Include a baseline view, comparison chart or schedule, and an assumptions history. Let users trace a proposed quantity or date back to its inputs. Keep forecasts distinct from actual results. Open with entity map; move into operating differences for the detailed task; finish in integration choices for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.





