Screenshot of the Transparent opportunity matching and shortlist platform interactive demo
Screenshot of the interactive demo, on sample data

Transparent opportunity matching and shortlist platform

Reduce shortlist rework while keeping the reasoning visible.

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For
Recruiters, talent teams and professional networkers matching people to roles and contacts
Solves
Generic match lists and opaque recommendations hide why a person or role fits, so shortlists need manual rework and outreach stalls.
Delivers
Reviewer-approved shortlists and outreach drafts linked to stated fit reasons
Built in
about 5 weeks of creation time, MVP in 6 days
Investment
$12,500 for the MVP, $42,500 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

Reduce shortlist rework while keeping the reasoning visible.

  1. Ingest permitted profiles, role requirements and preferences.
  2. Suggest collaborators, opportunities and professional contacts from stated criteria.
  3. Show why each suggested connection or opportunity fits.
  4. Prioritize meaningful work relationships over generic matches.
  5. Provide recommendations and analysis for next steps.
  6. Support an interactive chat that improves with use.
  7. Generate personalized introduction messages.
  8. Recommend industry professionals and hiring managers.
  9. Minimize travel time and cost for scheduling.
  10. Tailor planning to different industries and project types.
  11. Adjust routes and plans on changing conditions.
  12. Connect with mapping and scheduling platforms.
  13. Display routes and plans in a visual dashboard.
  14. Track outreach efforts and responses.
  15. Compare the reviewed result with the recorded baseline and value assumptions.
  16. Capture corrections and named-owner approval before consequential use.
  17. Export a versioned reviewer-approved shortlist and outreach set with source references and unresolved questions.

Everything these tools do, in one app

What goes in, what comes out

What the customer puts in
  • Permitted profiles
  • Role requirements
  • Location constraints
  • Outreach history

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

What the customer gets
  • Reviewer-approved shortlists
  • Outreach drafts linked to stated fit reasons
02

How it works

The workflow

  1. In
    Start with

    Permitted profiles, role requirements, location constraints and outreach history

  2. 1

    Confirm the buyer's problem and scope

  3. 2

    Collect permitted profiles

  4. 3

    Role requirements

  5. 4

    Location constraints and outreach history

  6. 5

    Then follow this sequence: 1

  7. Out
    Finish with

    Reviewer-approved shortlists and outreach drafts linked to stated fit reasons

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. One fixed role family and permitted data sources; final hiring and outreach decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Role and profile intake, Editable shortlist and outreach preview, Client proof and delivery. Use a thumbnail gallery for open roles and candidate pools, a large central matching canvas, and a right-hand panel for fit reasons, constraints and comments. Let users compare candidate versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant candidate or role. Make the task-specific outcome reviewer-approved shortlists and outreach drafts linked to stated fit reasons visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, profile versions, client comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Applicant tracking systems, professional networks, calendar and mapping services, and outreach mailboxes. Start with file exchange and validate destination specifications before promising direct posting or messaging. 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

    6 days

    One buyer segment, one recurring use case; first modules: ingest permitted profiles, role requirements and preferences; suggest collaborators, opportunities and professional contacts from stated criteria. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    7 days

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

  4. 4

    Full product

    3 weeks

    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 recruiters, talent teams and professional networkers matching people to roles and contacts use it to solve "generic match lists and opaque recommendations hide why a person or role fits, so shortlists need manual rework and outreach stalls"?
  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: Accepted shortlist entries per recruiting hour and follow-up replies per outreach batch.
  4. Measure, then decide. Track accepted shortlist entries per recruiting hour and follow-up replies per outreach batch; 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: One fixed role family and permitted data sources; final hiring and outreach decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: ingest permitted profiles, role requirements and preferences; suggest collaborators, opportunities and professional contacts from stated criteria. Support the third module with operator review: show why each suggested connection or opportunity fits. 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 reviewer-approved shortlists and outreach drafts linked to stated fit reasons. Retain the explicit scope boundary: One fixed role family and permitted data sources; final hiring and outreach decisions remain human.

What the build depends on. Profile upload and preview, asynchronous matching jobs, editable version history, reviewer access and tested export formats. High-fidelity matching requires specialist recruiting QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed role family and permitted data sources; final hiring and outreach decisions remain human.

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: ingest permitted profiles, role requirements and preferences; suggest collaborators, opportunities and professional contacts from stated criteria. Manual review in the loop.

    $12,500 · about 6 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.

    $12,500 · about 7 days of creation time

  3. Phase 3

    Full product

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

    $17,500 · about 3 weeks of creation time

Indicative total, MVP to full product$42,500about 5 weeks of creation time · start with the MVP from $12,500

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.

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

Recruiters, talent teams and professional networkers matching people to roles and contacts run it inside the business: permitted profiles, role requirements, location constraints and outreach history in, reviewer-approved shortlists and outreach drafts linked to stated fit reasons 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#279158
  • accent#c954a4
  • surface#e4f1ea
  • ink#22201e
Headings
DM Serif Display
Text
DM Sans
Voice
Fair, human, straightforward
Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined role family. Offer a monthly matching allowance after repeat demand. Quote complex multi-region or specialist sourcing separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewer-approved shortlist and outreach set. 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

Reduce shortlist rework while keeping the reasoning visible. Demonstrate a concrete reviewer-approved shortlist and outreach set using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Recruiters, talent teams and professional networkers matching people to roles and contacts professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewer-approved shortlist and outreach set from a small authorized input set, with a transparent calculation of accepted shortlist entries per recruiting hour and follow-up replies per outreach batch and no promised savings.

The first 30 days

  1. Week 1: interview five recruiters, talent teams and professional networkers matching people to roles and contacts and inspect a recent example of generic match lists and opaque recommendations hide why a person or role fits, so shortlists need manual rework and outreach stalls.
  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 accepted shortlist entries per recruiting hour and follow-up replies per outreach batch, 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: Accepted shortlist entries per recruiting hour and follow-up replies per outreach batch. 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

Accepted shortlist entries per recruiting hour and follow-up replies per outreach batch; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewer-approved shortlists and outreach drafts linked to stated fit reasons. 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 reusable library of approved fit criteria, outreach templates and review examples, together with reliable delivery for a narrow recruiting niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for recruiters, talent teams and professional networkers matching people to roles and contacts. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Ariadna, PathFinder and NetworkAI, plus manual sourcing, spreadsheets and generic job boards. Compare this product with the buyer's present method on accepted shortlist entries per recruiting hour and follow-up replies per outreach batch. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, profile enrichment, storage, reviewer hours, client revision rounds and licensed data sources. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewer-approved shortlists and outreach drafts linked to stated fit reasons. Track cost per accepted output, including correction work, unsuccessful cases and support.

06

Safeguards

Preserve candidate consent, source attribution, accuracy and usage permissions. Candidates and hiring owners approve substantive changes and outreach scope. One fixed role family and permitted data sources; final hiring and outreach decisions remain human. 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 6 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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