
Transparent opportunity matching and shortlist platform
Reduce application effort while keeping the applicant's own facts and choices visible.
- 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
What it does
Reduce application effort while keeping the applicant's own facts and choices visible.
- Import resume or CV.
- Import job descriptions.
- 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.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
- Export a versioned applicant-approved application package with source references and unresolved questions.
Everything these tools do, in one app
- Resume or CV input Lets you provide your resume or CV so the tool can use your background to personalize outputs.Found in Cover Letter AI, JobFlow, Sorce
- Job description input Lets you provide the job description so the tool can tailor the application materials to that role.Found in Cover Letter AI, JobFlow
- Cover letter generation Creates a cover letter for your application.Found in Cover Letter AI, JobFlow, Sorce
- Application-specific personalization Tailors the generated cover letter to the specific job or application.Found in Cover Letter AI, JobFlow, Sorce
- Multiple cover letter versions Produces several versions of the cover letter so you can refine and choose the one you prefer.Found in Cover Letter AI
- Writing style selection Lets you choose a preferred writing style for the cover letter.Found in Cover Letter AI
- Key skills highlighting Lets you specify key skills to focus on in the cover letter.Found in Cover Letter AI
- Company name input Lets you provide the company name for personalization.Found in Cover Letter AI
- Multilingual cover letters Generates cover letters in various languages.Found in Cover Letter AI
- Data privacy Keeps the information you provide private and does not store it on servers.Found in Cover Letter AI
- Job posting discovery Automatically finds job postings from multiple sources and centralizes them in one feed.Found in JobFlow
- AI match scoring Evaluates how well a role fits your profile and provides a match score.Found in JobFlow
- Personalized CV generation Generates a personalized CV for a specific job listing.Found in JobFlow
- Application pipeline tracking Tracks your applications from saved roles through to offers in one place.Found in JobFlow
- Regional market coverage Targets job markets in several European countries.Found in JobFlow
- Swipe-based applying Lets you browse and apply to jobs by swiping right to apply and left to skip.Found in Sorce
- Automatic form filling Automatically fills and submits application forms on company websites.Found in Sorce
- Activity metrics Provides simple metrics and usage feedback to track your application progress.Found in Sorce
What goes in, what comes out
- Resume or CV
- Job descriptions
- Company names
- Stated preferences
- Market targets
- Application history
AI drafts, people review. Transparent opportunity matching and shortlist platform.
- Applicant-approved cover letters
- Match shortlists
- Tracked applications
How it works
The workflow
- InStart with
Resume or CV, job descriptions, company names, stated preferences, market targets and application history
- 1
Confirm the buyer's problem and scope
- 2
Collect resume or CV
- 3
Job descriptions
- 4
Company names
- 5
Stated preferences and market targets
- 6
Then follow this sequence: 1
- OutFinish 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.
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
6 daysOne 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
Paid pilot
7 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
3 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 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"?
- 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 quality and outcome thresholds before the pilot using this measure: Shortlisted applications per hour and applicant corrections after submission.
- 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.
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: import resume or CV; import job descriptions. 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$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.
| 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
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.
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
- 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.
- Week 2: prepare a consented or synthetic demonstration of the task modules.
- Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
- 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.
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.