
Cross-functional terminology mediator
Resolve semantic handoff problems before they become delivery errors.
- For
- Managers coordinating technical and commercial teams
- Solves
- The same project terms mean different things to different teams.
- Delivers
- Cross-team agreed glossary
- Built in
- about 3 weeks of creation time, MVP in 3 days
- Investment
- $9,500 for the MVP, $32,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
For managers coordinating technical and commercial teams, turn approved documents and participant definitions into cross-team agreed glossary.
- Extract recurring terms.
- Compare stated meanings.
- Link conflict examples.
- Draft shared definitions.
- Capture owner approvals.
- Export project glossary.
What goes in, what comes out
- Approved documents
- Participant definitions
AI drafts, people review. Searchable structured library and data stewardship console.
- Cross-team agreed glossary
How it works
The workflow
- InStart with
Approved documents and participant definitions
- 1
The buyer creates a project
- 2
Supplies approved documents and participant definitions
- 3
Confirms scope and access
- OutFinish with
Cross-team agreed glossary
AI does the heavy lifting, people stay in charge
Cluster meanings without asserting one team is correct. 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.
What your team sees
Key screens: Term collection, Meaning comparison, Agreement glossary. Use a searchable table or visual gallery with filters for the domain’s important attributes. Open each item into a detail drawer containing source records, ownership and history. Put proposed merges and field changes in a separate review queue. Provide a preview before any bulk export. Open with term collection; move into meaning comparison for the detailed task; finish in agreement glossary for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.
Accounts and administration
Record ownership, access permissions, change proposals, original-value retention, version history, review dates, bulk import/export and duplicate resolution. Include organization-scoped access, named project owners, review queues, usage limits, export history and retention settings. Never reuse private customer material for other accounts without permission.
Integrations and data access
Team updates, calendars, project records and agreed management routines. Source systems, catalog exports and cloud file storage. Start with reversible CSV or file imports and validate identifiers before any direct writes. Begin with uploads and exports of approved documents and participant definitions. Any named system or connector is a candidate requiring current access and compatibility checks; no live connection is included by default.
How we build it
We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.
- 1
Scoping call
Day 1Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.
- 2
MVP
3 daysOne buyer segment, one recurring use case; first modules: extract recurring terms; compare stated meanings. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
4 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
7 daysSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.
Why we start with an MVP
An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.
- Pick the riskiest assumption. Here: will managers coordinating technical and commercial teams use it to solve "the same project terms mean different things to different teams"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Agree the acceptance criteria, input limits and reviewer responsibilities before starting.
- Measure, then decide. Track terminology disputes and handoff corrections. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Costed pilot: One initiative with human-approved definitions. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: extract recurring terms; compare stated meanings. Support the third task through an assisted review queue: link conflict examples. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of cross-team agreed glossary. 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.
After the MVP. After paying customers repeatedly accept cross-team agreed glossary, automate draft shared definitions; capture owner approvals; export project glossary. Add one tested read integration, reusable customer configuration and scheduled repeat delivery. Increase supported formats or teams only when evaluation cases and reviewer capacity cover the new scope. One initiative with human-approved definitions.
What the build depends on. Stable identifiers, an agreed data schema, reversible imports, mapping review and source ownership. Data quality work can exceed model development effort. Obtain representative authorized inputs, an agreed review rubric and a buyer-side owner. Specific scope: One initiative with human-approved definitions.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case; first modules: extract recurring terms; compare stated meanings. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$32,500about 3 weeks of creation time · start with the MVP from $9,500
Running costs per month
A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $30–$60 | $50–$100 | $80–$160 |
| Full productabout 50 customers | $110–$210 | $350–$700 | $460–$910 |
Run it or resell it
For your own team
Managers coordinating technical and commercial teams run it inside the business: approved documents and participant definitions in, cross-team agreed glossary out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#275191 - accent
#c99354 - surface
#e4e9f1 - ink
#22201e
- Headings
- Libre Baskerville
- Text
- IBM Plex Sans
- Voice
- Practical, organised, candid
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 500-2,500 for one collection cleanup and launch, followed by USD 100-500 monthly for maintenance within agreed record limits. Larger migrations and complex rights management are separately scoped. Prices are hypotheses. For this buyer, package the first sale around reconcile fifteen project terms and the defined cross-team agreed glossary. Record actual review effort before offering a recurring allowance. The commercial pilot fee is distinct from the platform development budget.
Message to test
Resolve semantic handoff problems before they become delivery errors. Demonstrate the result with reconcile fifteen project terms for managers coordinating technical and commercial teams. Use a concrete before-and-after example without promising unmeasured savings.
Where to find buyers
Product operations groups and management trainers
Lead magnet
Reconcile fifteen project terms
The first 30 days
- Week 1: interview five prospective buyers from managers coordinating technical and commercial teams and inspect how they handle the same project terms mean different things to different teams.
- Week 2: prepare reconcile fifteen project terms using authorized or synthetic material.
- Week 3: share the demonstration through product operations groups and management trainers and seek one bounded paid pilot.
- Week 4: measure terminology disputes and handoff corrections, review delivery effort and ask for a repeat purchase. This is a validation schedule, not a promise that the full product can be built in thirty days.
Paid pilot
Agree the acceptance criteria, input limits and reviewer responsibilities before starting. Run reconcile fifteen project terms and deliver cross-team agreed glossary. Compare terminology disputes and handoff corrections with the buyer's current process on comparable cases; include corrections, missed issues and reviewer time. Seek payment and repeat use. Stop or revise the scope if data access, accuracy or unit economics fail.
Success metrics
Terminology disputes and handoff corrections
Retention and expansion
Build repeat use around cross-team agreed glossary. Save approved configurations and review decisions with permission, revisit unresolved exceptions and show progress on terminology disputes and handoff corrections. Offer a recurring volume allowance after repeat demand; expand to adjacent tasks only when the buyer asks and delivery quality remains acceptable.
Why clients would pick it
A useful niche taxonomy, customer-approved mappings and accumulated correction history that improve retrieval and reduce repeated cleanup. For this concept, accumulate permissioned examples and reviewer corrections around resolve semantic handoff problems before they become delivery errors. The durable asset is reliable task-specific execution and trusted customer configuration, not access to a general-purpose AI model.
Alternatives and positioning
Spreadsheets, shared folders, existing asset or information management systems and manual data cleanup. Position this concept around resolve semantic handoff problems before they become delivery errors. Compare it against the customer's current process on the same representative task. This is proposed differentiation; no exhaustive competitor study or uniqueness claim has been established.
Main delivery costs
Import cleanup, extraction, storage, indexing, steward review, duplicate investigation and recurring source updates. Initial validation additionally budgets for facilitated terminology workshop. Track model usage, storage, reviewer minutes, exception handling and customer support per accepted deliverable.
Safeguards
Confirm owners, decisions and commitments. Keep employee discussion notes access-controlled and avoid covert individual performance inference. One initiative with human-approved definitions. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.