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 application effort while keeping the applicant's own facts and choices visible.

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For
Job seekers and career changers applying to many roles across several markets
Solves
Applications are scattered across tools, cover letters are generic, and match decisions are opaque.
Delivers
Applicant-approved cover letters, match shortlists and tracked applications
Built in
about 5 weeks of creation time, MVP in 6 days
Investment
$13,500 for the MVP, $46,000 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

Reduce application effort while keeping the applicant's own facts and choices visible.

  1. Import resume or CV.
  2. Import job descriptions.
  3. Discover job postings from multiple sources into one feed.
  4. Score each role against the profile with visible reasons.
  5. Generate a cover letter for the selected role.
  6. Personalize the letter to the company and application.
  7. Produce several cover letter versions.
  8. Select a preferred writing style.
  9. Highlight specified key skills.
  10. Generate a personalized CV for a specific listing.
  11. Generate cover letters in several languages.
  12. Track applications from saved roles through to offers.
  13. Support regional job markets in several European countries.
  14. Allow swipe-based browsing and applying.
  15. Fill and submit application forms on company websites.
  16. Show simple activity metrics and usage feedback.
  17. Keep supplied data private and unstored on servers where selected.
  18. Compare the reviewed result with the recorded baseline and value assumptions.
  19. Capture corrections and named-owner approval before consequential use.
  20. Export a versioned applicant-approved application package with source references and unresolved questions.

Everything these tools do, in one app

What goes in, what comes out

What the customer puts in
  • Resume or CV
  • Job descriptions
  • Company names
  • Stated preferences
  • Market targets
  • Application history

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

What the customer gets
  • Applicant-approved cover letters
  • Match shortlists
  • Tracked applications
02

How it works

The workflow

  1. In
    Start with

    Resume or CV, job descriptions, company names, stated preferences, market targets and application history

  2. 1

    Confirm the buyer's problem and scope

  3. 2

    Collect resume or CV

  4. 3

    Job descriptions

  5. 4

    Company names

  6. 5

    Stated preferences and market targets

  7. 6

    Then follow this sequence: 1

  8. Out
    Finish with

    Applicant-approved cover letters, match shortlists and tracked applications

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final factual accuracy, employer-specific claims and submission decisions remain with the applicant. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Profile and preferences, Opportunity feed and shortlist, Application workspace. Use a card list for discovered roles, a large central editor for cover letters and CVs, and a right-hand panel for match evidence, skills and comments. Let users compare cover letter versions side by side. Display saved, applied, interview and offer states. Provide a shareable shortlist link with comments anchored to the relevant role. Make the task-specific outcome applicant-approved cover letters, match shortlists and tracked applications visible beside its evidence, review state and value baseline.

Accounts and administration

Profile ownership, document versions, match evidence, approval states, usage allowances, submission 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-owned resumes and CVs, authorized job boards and permitted company career pages. Cloud document storage, form-fill destinations and application tracking exports. Start with file exchange and validate destination specifications before promising direct submission. 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: import resume or CV; import job descriptions. 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 job seekers and career changers applying to many roles across several markets use it to solve "applications are scattered across tools, cover letters are generic, and match decisions are opaque"?
  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: Shortlisted applications per hour and applicant corrections after submission.
  4. Measure, then decide. Track shortlisted applications per hour and applicant corrections after submission; 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 applicant profile, one market and one language; final factual accuracy and submission decisions remain with the applicant. Implement one approved input format, a bounded representative case set and the first two task modules: import resume or CV; import job descriptions. Support the remaining modules with operator review: discover job postings from multiple sources into one feed; score each role against the profile with visible reasons; generate a cover letter for the selected role; personalize the letter to the company and application; produce several cover letter versions; select a preferred writing style; highlight specified key skills; generate a personalized CV for a specific listing; generate cover letters in several languages; track applications from saved roles through to offers; support regional job markets in several European countries; allow swipe-based browsing and applying; fill and submit application forms on company websites; show simple activity metrics and usage feedback; keep supplied data private and unstored on servers where selected. 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 applicant-approved cover letters, match shortlists and tracked applications. Retain the explicit scope boundary: One applicant profile, one market and one language; final factual accuracy and submission decisions remain with the applicant.

What the build depends on. Document upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity submission requires specialist recruitment QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One applicant profile, one market and one language; final factual accuracy and submission decisions remain with the applicant.

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: import resume or CV; import job descriptions. Manual review in the loop.

    $13,500 · 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.

    $13,500 · about 7 days of creation time

  3. Phase 3

    Full product

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

    $19,000 · about 3 weeks of creation time

Indicative total, MVP to full product$46,000about 5 weeks of creation time · start with the MVP from $13,500

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

Job seekers and career changers applying to many roles across several markets run it inside the business: resume or CV, job descriptions, company names, stated preferences, market targets and application history in, applicant-approved cover letters, match shortlists and tracked applications 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#279178
  • accent#c95468
  • surface#e4f1ee
  • 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 applicant package. Offer a monthly application allowance after repeat demand. Quote complex multi-market or specialist recruitment workflows separately. These are test prices, not market benchmarks. Package the initial sale as one bounded applicant-approved application package. 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 application effort while keeping the applicant's own facts and choices visible. Demonstrate a concrete applicant-approved application package using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Job seekers and career changers professional communities; specialist career consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample applicant-approved application package from a small authorized input set, with a transparent calculation of shortlisted applications per hour and applicant corrections after submission and no promised savings.

The first 30 days

  1. Week 1: interview five job seekers and career changers applying to many roles across several markets and inspect a recent example of applications scattered across tools, generic cover letters and opaque match decisions.
  2. Week 2: prepare a consented or synthetic demonstration of the task modules.
  3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
  4. Week 4: measure shortlisted applications per hour and applicant corrections after submission, 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: Shortlisted applications per hour and applicant corrections after submission. 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

Shortlisted applications per hour and applicant corrections after submission; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs applicant-approved application packages. 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 writing styles, match criteria and review examples, together with reliable delivery for a narrow applicant niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for job seekers and career changers applying to many roles across several markets. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Cover Letter AI, JobFlow, Sorce, freelancers and generic writing tools. Compare this product with the buyer's present method on shortlisted applications per hour and applicant corrections after submission. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, document processing, storage, reviewer hours, applicant revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of applicant-approved application packages. Track cost per accepted output, including correction work, unsuccessful cases and support.

06

Safeguards

Preserve applicant voice, source attribution, factual accuracy and usage permissions. Applicants approve substantive changes and submission scope. One applicant profile, one market and one language; final factual accuracy and submission decisions remain with the applicant. 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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