Research contributor agreement tracker
Discuss contribution expectations early with a traceable record.
- For
- Multi-institution research coordinators
- Solves
- Contribution expectations are unclear until publication approaches.
- Delivers
- Team-approved contribution record
- Built in
- about 4 weeks of creation time, MVP in 5 days
- Investment
- $11,500 for the MVP, $39,000 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
For multi-institution research coordinators, turn team-approved contribution statements and project milestones into team-approved contribution record.
- Capture agreed roles.
- Link completed contributions.
- Flag unresolved expectations.
- Draft review agendas.
- Record team decisions.
- Export contribution summaries.
What goes in, what comes out
- Team-approved contribution statements
- Project milestones
AI drafts, people review. Operational coordination portal.
- Team-approved contribution record
How it works
The workflow
- InStart with
Team-approved contribution statements and project milestones
- 1
The buyer creates a project
- 2
Supplies team-approved contribution statements and project milestones
- 3
Confirms scope and access
- OutFinish with
Team-approved contribution record
AI does the heavy lifting, people stay in charge
Summarize declared contributions without judging scientific worth. 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: Contribution plan, Update evidence, Team review. Use a queue or timeline as the opening view, with clear owners, dates and current states. Each case opens into its source context, proposed actions and discussion. Give external participants a limited form or status page. Make the next required action visible without opening every record. Open with contribution plan; move into update evidence for the detailed task; finish in team review for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.
Accounts and administration
Role permissions, task ownership, deadlines, reminders, approval gates, exception handling, action history, duplicate prevention and reversible configuration. 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
Authorized datasets, papers, protocols, code and research records. Calendars, email, task managers and relevant business records. Use draft actions and supervised handoffs first, then enable only specifically authorized writes. Begin with uploads and exports of team-approved contribution statements and project milestones. 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
5 daysOne buyer segment, one recurring use case; first modules: capture agreed roles; link completed contributions. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
6 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
2 weeksSelf-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 multi-institution research coordinators use it to solve "contribution expectations are unclear until publication approaches"?
- 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 unresolved role expectations and documentation completeness. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Costed pilot: Administrative record; no automated authorship entitlement decisions. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: capture agreed roles; link completed contributions. Support the third task through an assisted review queue: flag unresolved expectations. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of team-approved contribution record. 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 team-approved contribution record, automate draft review agendas; record team decisions; export contribution summaries. 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. Administrative record; no automated authorship entitlement decisions.
What the build depends on. Explicit state definitions, owner mapping, approval rules, idempotent actions, notifications and recovery procedures. Workflow reliability matters more than fluent text. Obtain representative authorized inputs, an agreed review rubric and a buyer-side owner. Specific scope: Administrative record; no automated authorship entitlement decisions.
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: capture agreed roles; link completed contributions. 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$39,000about 4 weeks of creation time · start with the MVP from $11,500
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 | $40–$90 | $70–$150 |
| Full productabout 50 customers | $110–$210 | $280–$560 | $390–$770 |
Run it or resell it
For your own team
Multi-institution research coordinators run it inside the business: team-approved contribution statements and project milestones in, team-approved contribution record 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
#912743 - accent
#54c9aa - surface
#f1e4e8 - ink
#22201e
- Headings
- DM Serif Display
- Text
- DM Sans
- Voice
- Rigorous, transparent, cited
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 750-2,500 setup plus USD 200-800 monthly for one bounded workflow and team. Cap case volume and implementation scope. Larger operational integrations need separate quotes. Prices are hypotheses. For this buyer, package the first sale around coordinate one research team's contribution review and the defined team-approved contribution record. Record actual review effort before offering a recurring allowance. The commercial pilot fee is distinct from the platform development budget.
Message to test
Discuss contribution expectations early with a traceable record. Demonstrate the result with coordinate one research team's contribution review for multi-institution research coordinators. Use a concrete before-and-after example without promising unmeasured savings.
Where to find buyers
Research project offices and collaboration networks
Lead magnet
Coordinate one research team's contribution review
The first 30 days
- Week 1: interview five prospective buyers from multi-institution research coordinators and inspect how they handle contribution expectations are unclear until publication approaches.
- Week 2: prepare coordinate one research team's contribution review using authorized or synthetic material.
- Week 3: share the demonstration through research project offices and collaboration networks and seek one bounded paid pilot.
- Week 4: measure unresolved role expectations and documentation completeness, 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 coordinate one research team's contribution review and deliver team-approved contribution record. Compare unresolved role expectations and documentation completeness 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
Unresolved role expectations and documentation completeness
Retention and expansion
Build repeat use around team-approved contribution record. Save approved configurations and review decisions with permission, revisit unresolved exceptions and show progress on unresolved role expectations and documentation completeness. 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
Customer-specific workflow rules, reliable handoffs, operational history and integrations that make the service part of daily work. For this concept, accumulate permissioned examples and reviewer corrections around discuss contribution expectations early with a traceable record. The durable asset is reliable task-specific execution and trusted customer configuration, not access to a general-purpose AI model.
Alternatives and positioning
Shared inboxes, spreadsheets, task boards and existing workflow automation products. Position this concept around discuss contribution expectations early with a traceable record. 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
Workflow configuration, integration maintenance, model calls, notification delivery, exception support and monitoring. Initial validation additionally budgets for research governance facilitation. Track model usage, storage, reviewer minutes, exception handling and customer support per accepted deliverable.
Safeguards
Preserve original data, methods, citations and research limitations. Use researcher review and document every substantive transformation. Administrative record; no automated authorship entitlement decisions. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.