Pro bono matter scope planner

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.

1. Pick the riskiest assumption. Here: will legal aid clinic coordinators use it to solve "volunteer capacity is allocated before matter scope is clear"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree the acceptance criteria, input limits and reviewer responsibilities before starting.
4. Measure, then decide. Track incomplete scope and assignment preparation time. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Costed pilot: No legal advice or automated client eligibility decisions. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: structure stated requests; identify missing facts. Support the third task through an assisted review queue: draft task boundaries. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of supervisor-approved pro bono scope pack. 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 supervisor-approved pro bono scope pack, automate map volunteer availability; record supervisor choices; export engagement checklist. 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. No legal advice or automated client eligibility decisions.

What the build depends on. A defensible calculation model, explicit units, constraint validation and representative boundary tests. Advanced forecasting or optimization needs adequate historical data. Obtain representative authorized inputs, an agreed review rubric and a buyer-side owner. Specific scope: No legal advice or automated client eligibility decisions.

Pricing to test

Test USD 750-3,000 for a scoped planning setup and review, then USD 200-900 monthly for refreshes within agreed complexity. Data integration and optimization are separately scoped. All ranges are hypotheses. For this buyer, package the first sale around scope five synthetic matters and the defined supervisor-approved pro bono scope pack. Record actual review effort before offering a recurring allowance. The commercial pilot fee is distinct from the platform development budget.

Message to test

Make supervised volunteer scope explicit before assignment. Demonstrate the result with scope five synthetic matters for legal aid clinic coordinators. Use a concrete before-and-after example without promising unmeasured savings.

Where to find buyers

Legal aid networks and law school clinics

Lead magnet

Scope five synthetic matters

The first 30 days

1. Week 1: interview five prospective buyers from legal aid clinic coordinators and inspect how they handle volunteer capacity is allocated before matter scope is clear.
2. Week 2: prepare scope five synthetic matters using authorized or synthetic material.
3. Week 3: share the demonstration through legal aid networks and law school clinics and seek one bounded paid pilot.
4. Week 4: measure incomplete scope and assignment preparation time, 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 scope five synthetic matters and deliver supervisor-approved pro bono scope pack. Compare incomplete scope and assignment preparation time 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

Incomplete scope and assignment preparation time

Retention and expansion

Build repeat use around supervisor-approved pro bono scope pack. Save approved configurations and review decisions with permission, revisit unresolved exceptions and show progress on incomplete scope and assignment preparation time. 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 validated domain model, customer-approved constraints and forecast or decision history that improves practical planning. For this concept, accumulate permissioned examples and reviewer corrections around make supervised volunteer scope explicit before assignment. The durable asset is reliable task-specific execution and trusted customer configuration, not access to a general-purpose AI model.

Alternatives and positioning

Spreadsheets, planners, specialist forecasting tools and existing scheduling or configuration software. Position this concept around make supervised volunteer scope explicit before assignment. 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

Data preparation, domain modeling, validation, scenario computation, reviewer support and ongoing assumption maintenance. Initial validation additionally budgets for supervising lawyer review. Track model usage, storage, reviewer minutes, exception handling and customer support per accepted deliverable.