Screenshot of the Mentor capacity allocation co-op interactive demo
Screenshot of the interactive demo, on sample data

Mentor capacity allocation co-op

Increase useful mentoring access without overusing individuals.

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For
Professional development programs
Solves
Mentors are overloaded while suitable group sessions are underused.
Delivers
Participant-approved mentoring cohort
Built in
about 4 weeks of creation time, MVP in 4 days
Investment
$24,000 for the MVP, $50,000 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

Increase useful mentoring access without overusing individuals.

  1. Cluster compatible learning needs.
  2. Match group formats.
  3. Schedule mutually accepted sessions.
  4. Compare the reviewed result with the recorded baseline and value assumptions.
  5. Capture corrections and named-owner approval before consequential use.
  6. Export a versioned participant-approved mentoring cohort with source references and unresolved questions.

What goes in, what comes out

What the customer puts in
  • Opted-in goals
  • Mentor-declared expertise

AI drafts, people review. Transparent opportunity matching and shortlist platform.

What the customer gets
  • Participant-approved mentoring cohort
02

How it works

The workflow

  1. In
    Start with

    Opted-in goals and mentor-declared expertise

  2. 1

    Confirm the buyer's problem and scope

  3. 2

    Collect opted-in goals and mentor-declared expertise

  4. 3

    Then follow this sequence: 1

  5. Out
    Finish with

    Participant-approved mentoring cohort

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. No personality or demographic inference; participants control matching. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Verified offer or need profiles, Explainable match comparison, Mutual approval and handoff. Open with a filterable opportunity feed and clear fit explanations. Each profile shows source evidence, eligibility conditions and missing information. Keep saved, rejected and needs-review states. Include a deadline or next-action view without hiding the basis of recommendations. Make the task-specific outcome participant-approved mentoring cohort visible beside its evidence, review state and value baseline.

Accounts and administration

Editable criteria, dated sources, eligibility evidence, missing-data flags, saved shortlists, rejection reasons, deadline alerts and owner follow-up. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Approved HR documents, employee directories and learning records. Permitted opportunity feeds, customer profiles, calendars and CRM exports. Keep initial outreach or applications as user-reviewed drafts. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

03

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. 1

    Scoping call

    Day 1

    Thirty 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. 2

    MVP

    4 days

    One buyer segment, one recurring use case; first modules: cluster compatible learning needs; match group formats. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    5 days

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

  4. 4

    Full product

    9 days

    Self-serve onboarding, billing, monitoring and the wider integration set.

  5. 5

    Run and improve

    Monthly

    We 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.

  1. Pick the riskiest assumption. Here: will professional development programs use it to solve "mentors are overloaded while suitable group sessions are underused"?
  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 quality and outcome thresholds before the pilot using this measure: Useful mentoring sessions per mentor hour minus coordination cost.
  4. Measure, then decide. Track useful mentoring sessions per mentor hour minus coordination cost; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: No personality or demographic inference; participants control matching. Implement one approved input format, a bounded representative case set and the first two task modules: cluster compatible learning needs; match group formats. Support the third module with operator review: schedule mutually accepted sessions. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around participant-approved mentoring cohort. Retain the explicit scope boundary: No personality or demographic inference; participants control matching.

What the build depends on. Current source information, explicit eligibility rules, entity identity checks and inspectable fit reasoning. Sparse evidence limits match quality. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: No personality or demographic inference; participants control matching.

04

Investment

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

  1. Phase 1

    MVP

    One buyer segment, one recurring use case; first modules: cluster compatible learning needs; match group formats. Manual review in the loop.

    $24,000 · about 4 days of creation time

  2. Phase 2

    Paid pilot

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

    $11,000 · about 5 days of creation time

  3. Phase 3

    Full product

    Self-serve onboarding, billing, monitoring and the wider integration set.

    $15,000 · about 9 days of creation time

Indicative total, MVP to full product$50,000about 4 weeks of creation time · start with the MVP from $24,000

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.

StageHosting and infrastructureAI usageTotal per month
MVP and paid pilotabout 3 customers$30–$60$40–$90$70–$150
Full productabout 50 customers$110–$210$280–$560$390–$770
05

Run it or resell it

Internally

For your own team

Professional development programs run it inside the business: opted-in goals and mentor-declared expertise in, participant-approved mentoring cohort out, reviewed by your people.

For your clients

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#279151
  • accent#c954a0
  • surface#e4f1e9
  • ink#22201e
Headings
Fraunces
Text
Inter
Voice
Fair, human, straightforward
Selling it to your own clients: the go-to-market playbook

Pricing to test

Test USD 150-600 monthly for one narrow opportunity feed, or USD 750-2,500 for a bespoke researched shortlist. Price manual verification and custom research explicitly. These are pricing hypotheses. Package the initial sale as one bounded participant-approved mentoring cohort. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Increase useful mentoring access without overusing individuals. Demonstrate a concrete participant-approved mentoring cohort using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Professional development programs professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample participant-approved mentoring cohort from a small authorized input set, with a transparent calculation of useful mentoring sessions per mentor hour minus coordination cost and no promised savings.

The first 30 days

  1. Week 1: interview five professional development programs and inspect a recent example of mentors are overloaded while suitable group sessions are underused.
  2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
  3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
  4. Week 4: measure useful mentoring sessions per mentor hour minus coordination cost, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Useful mentoring sessions per mentor hour minus coordination cost. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Useful mentoring sessions per mentor hour minus coordination cost; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs participant-approved mentoring cohort. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A maintained niche opportunity dataset and documented relevance feedback, supported by relationships with the intended buyer community. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for professional development programs. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Manual research, directories, generic databases, referrals and existing opportunity marketplaces. Compare this product with the buyer's present method on useful mentoring sessions per mentor hour minus coordination cost. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Source collection, profile updates, entity resolution, eligibility verification, analyst research and customer feedback review. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of participant-approved mentoring cohort. Track cost per accepted output, including correction work, unsuccessful cases and support.

06

Safeguards

Keep employee data access explicit and confidential. Use human judgment for personnel decisions and do not infer protected traits or hidden personal characteristics. No personality or demographic inference; participants control matching. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

Get this solution built

Built for you by our AI software factory, MVP in about 4 days. Tell us about your business and how you want to run it: inside your company, or as part of what you offer your clients. We reply within one working day.

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