Transparent candidate screening and shortlist workbench

For

Recruiters and hiring managers screening candidates for defined roles

Solves

Candidate screening, interviews, scoring and shortlisting are split across several rented tools, so evidence and decisions are hard to trace.

Delivers

Reviewer-approved ranked shortlist linked to transcript evidence

Built in

about 4 weeks of creation time, MVP in 5 days

Investment

$14,500 for the MVP, $49,500 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce screening and shortlisting effort while keeping every score traceable to evidence.

1. Capture role intake and map key competencies.
2. Screen and rank applicants against stated skills and experience.
3. Run asynchronous AI interviews with text, audio or video answers.
4. Apply recruiter-set evaluation prompts and templates.
5. Generate role-specific quizzes and behavioral assessments.
6. Schedule interviews with calendar integration.
7. Transcribe interviews with timestamped quotes.
8. Produce decision-ready scorecards with highlighted evidence.
9. Support live interviews with prompts and structured notes.
10. Compare candidates side by side against the same criteria.
11. Collect collaborative team feedback and ratings.
12. Search permitted talent sources for sourcing.
13. Show performance and pipeline analytics.
14. Send personalized feedback to applicants.
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 ranked shortlist linked to transcript evidence with source references and unresolved questions.

Everything these tools do, in one app

• AI candidate screening Automatically evaluates and ranks applicants based on skills and experience.Found in hiring.studio
• AI interviews Conducts automated interviews with candidates, often asynchronously.Found in Foundire, Equip AI Interview, Potis 2.0 and 1 more
• Multi-format responses Allows candidates to answer in text, audio, or video formats.Found in Equip AI Interview
• Custom evaluation prompts Lets recruiters set prompts to guide AI scoring.Found in Equip AI Interview
• Automated ranking Ranks candidates automatically to identify top performers.Found in Equip AI Interview
• Quiz creation Enables creation of tailored quizzes for different roles.Found in Equip AI Interview
• Decision-ready scorecards Generates scorecards with transcripts and highlighted evidence.Found in Foundire
• Global talent search Searches a large database of professional profiles for sourcing.Found in Foundire
• Live interview copilot Provides real-time prompts and structured notes during interviews.Found in Foundire
• End-to-end hiring workflow Links sourcing, interviews, offers, and background checks in one platform.Found in Foundire
• Automated interview scheduling Schedules interviews automatically with calendar integration.Found in hiring.studio
• Customizable evaluation templates Provides templates to standardize candidate assessments.Found in hiring.studio
• Collaborative hiring tools Allows team members to share feedback and rate candidates.Found in hiring.studio
• Analytics dashboard Offers insights on recruitment metrics and bottlenecks.Found in hiring.studio
• Role intake and competency mapping Guides defining key competencies for a role.Found in Lavalier AI
• Interview scripting and live guidance Auto-generates questions and follow-ups to keep interviews on track.Found in Lavalier AI
• Transcription and timestamped quotes Converts speech to text with links to original transcript for verification.Found in Lavalier AI
• Evidence-linked summaries Provides AI-generated highlights tied to specific moments in the conversation.Found in Lavalier AI
• Candidate comparison Shows side-by-side views to evaluate candidates against the same criteria.Found in Lavalier AI
• Behavioral assessments Uses models like STAR to evaluate candidate responses to scenarios.Found in Potis 2.0
• Interview recording and summaries Records interviews and provides summaries for consistent comparison.Found in Potis 2.0
• Remote hiring support Adapts to different accents and languages for remote teams.Found in Potis 2.0
• Candidate engagement Keeps candidates engaged throughout the hiring process.Found in Potis 2.0
• Data visualization Displays candidate performance as a heat map for quick analysis.Found in Potis.AI
• Custom feedback Delivers personalized advice to each applicant.Found in Potis.AI
• Integration and teamwork Integrates with existing workflows and APIs for team access.Found in Potis.AI

What goes in, what comes out

The workflow

1. In
   Start with

   Role intake, candidate applications, interview recordings and assessment criteria

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect role intake

4. 3

   Candidate applications

5. 4

   Interview recordings and assessment criteria

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewer-approved ranked shortlist linked to transcript evidence

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 scoring arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One defined role family and one interview format; final hiring decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Role intake and criteria, Candidate pipeline and evidence, Shortlist and decision. Use a thumbnail gallery for roles, a large central candidate view, and a right-hand panel for criteria, evidence and comments. Let users compare candidates side by side. Display screened, interviewed, reviewed and shortlisted states. Provide a hiring-manager preview link with comments anchored to the relevant transcript moment. Make the task-specific outcome reviewer-approved ranked shortlist linked to transcript evidence visible beside its evidence, review state and value baseline.

Accounts and administration

Role ownership, candidate records, consent and retention states, reviewer access, scorecard versions, client comments, approval states, usage allowances, export 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, calendars, job boards and authorized talent sources. Cloud storage, video interview import/export and HRIS destinations. Start with file exchange and validate destination specifications before promising direct write-back. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

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

   5 days

   One buyer segment, one recurring use case; first modules: capture role intake and map key competencies; screen and rank applicants against stated skills and experience. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

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

4. 4

   Full product

   2 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 and hiring managers screening candidates for defined roles use it to solve "candidate screening, interviews, scoring and shortlisting are split across several rented tools, so evidence and decisions are hard to trace"?
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 shortlists per recruiter hour and corrections after hiring-manager review.
4. Measure, then decide. Track accepted shortlists per recruiter hour and corrections after hiring-manager review; 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 defined role family and one interview format; final hiring decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: capture role intake and map key competencies; screen and rank applicants against stated skills and experience. Support the third module with operator review: run asynchronous AI interviews with text, audio or video answers. 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 roles and candidate volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewer-approved ranked shortlist linked to transcript evidence. Retain the explicit scope boundary: One defined role family and one interview format; final hiring decisions remain human.

What the build depends on. Candidate consent and retention rules, interview recording and preview, asynchronous processing jobs, editable scorecard history, reviewer access and tested export formats. High-fidelity hiring support requires qualified human review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One defined role family and one interview format; final hiring decisions remain human.

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

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.

Your brand, or this one

Run it under your own brand, or start from this concept style.

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 package. Offer a monthly screening allowance after repeat demand. Quote complex multi-role or multi-language hiring separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewer-approved ranked shortlist linked to transcript evidence. 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 screening and shortlisting effort while keeping every score traceable to evidence. Demonstrate a concrete reviewer-approved ranked shortlist linked to transcript evidence using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Recruiters and hiring managers screening candidates for defined roles 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 ranked shortlist linked to transcript evidence from a small authorized input set, with a transparent calculation of accepted shortlists per recruiter hour and corrections after hiring-manager review and no promised savings.

The first 30 days

1. Week 1: interview five recruiters and hiring managers screening candidates for defined roles and inspect a recent example of candidate screening, interviews, scoring and shortlisting split across several rented tools.
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 shortlists per recruiter hour and corrections after hiring-manager review, 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 shortlists per recruiter hour and corrections after hiring-manager review. 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 candidate consent 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 shortlists per recruiter hour and corrections after hiring-manager review; 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 ranked shortlist linked to transcript evidence. 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 role criteria, interview templates and review examples, together with reliable delivery for a narrow hiring niche. Build a permissioned library of representative role cases, reviewer corrections and verified operating constraints for recruiters and hiring managers screening candidates for defined roles. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

DeepMate, Foundire, Equip AI Interview, hiring.studio, Lavalier AI, Potis 2.0 and Potis.AI, plus manual screening and spreadsheets. Compare this product with the buyer's present method on accepted shortlists per recruiter hour and corrections after hiring-manager review. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Interview processing, transcription, storage, reviewer hours, candidate support and licensed assessment content. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewer-approved ranked shortlist linked to transcript evidence. Track cost per accepted shortlist, including correction work, unsuccessful cases and support.

Preserve candidate consent, data retention limits, source attribution and assessment fairness. Hiring managers approve shortlists and hiring decisions. One defined role family and one interview format; final hiring decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.