Transparent candidate sourcing and shortlist workbench

For

Recruiters and hiring managers filling repeated role types

Solves

Candidate sourcing, screening and scheduling are split across several tools, and match decisions cannot be explained or overridden.

Delivers

Recruiter-approved shortlists linked to evidence

Built in

about 4 weeks of creation time, MVP in 5 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

Reduce manual screening and coordination while keeping every match decision explainable and recruiter-approved.

1. Source candidates from authorized channels.
2. Screen and evaluate candidate profiles.
3. Match candidates to role requirements and preferences.
4. Generate job descriptions and ideal candidate profiles.
5. Model candidate personas with goals, constraints and skills.
6. Require supporting evidence for resume claims.
7. Run AI-driven technical assessments.
8. Show why each match was recommended.
9. Let recruiters override match decisions.
10. Schedule interviews and coordinate calendars.
11. Manage candidate follow-up and communication.
12. Support Slack-first task instructions.
13. Sync with applicant tracking systems.
14. Learn from recruiter feedback over time.
15. Export a versioned recruiter-approved shortlist linked to evidence with source references and unresolved questions.

Everything these tools do, in one app

• AI candidate sourcing Automatically finds and sources potential candidates for open roles.Found in Contrario, Bolto
• Automated candidate screening Uses AI to screen and evaluate candidates, reducing manual review.Found in Contrario, Donna AI, Bolto
• AI-driven matching Matches candidates to job descriptions or roles based on profile data and preferences.Found in Donna AI, Roster, Bolto
• Interview scheduling Automates the coordination and scheduling of interviews.Found in Contrario
• Candidate follow-up Manages communication and follow-ups with candidates throughout the hiring process.Found in Contrario
• Slack-first interaction Allows users to manage hiring tasks and instruct agents using natural language inside Slack.Found in Contrario
• Job description generation Generates job descriptions and ideal candidate profiles.Found in Contrario
• ATS integrations Connects with applicant tracking systems to maintain existing hiring infrastructure.Found in Contrario
• Feedback-driven learning Learns hiring preferences over time to refine candidate suggestions.Found in Contrario
• Personal AI agents AI agents represent candidates and recruiters, communicating on their behalf.Found in Donna AI
• Persona modeling Creates structured profiles capturing goals, constraints, skills, and role preferences.Found in Donna AI
• Candidate verification Requires supporting evidence for resume claims to improve trust.Found in Donna AI
• Transparent reasoning Provides audit trails so recruiters can see why a match was recommended and override decisions.Found in Donna AI
• Job posting and curated matches Allows posting jobs and receiving curated candidate matches, reducing application sifting.Found in Roster
• Fast hiring turnaround Promises to find a suitable match within a short timeframe (e.g., 72 hours).Found in Roster
• Technical assessments Evaluates candidates' skills through AI-driven technical assessments.Found in Bolto
• Interview management Provides an integrated platform for conducting interviews and managing candidate profiles.Found in Bolto
• Payroll and HR management Handles employee payments and administration within the same platform.Found in Bolto

What goes in, what comes out

The workflow

1. In
   Start with

   Authorized role requirements, candidate profiles, assessment results and hiring constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect authorized role requirements

4. 3

   Candidate profiles

5. 4

   Assessment results and hiring constraints

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Recruiter-approved shortlists linked to evidence

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate matches and shortlist drafts for the stated task modules. Use deterministic code for scoring rules, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed role family and authorized sourcing channels; final hiring decisions and employment terms remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Role brief and constraints, Editable shortlist preview, Candidate evidence and delivery. Use a thumbnail gallery for open roles, a large central shortlist canvas, and a right-hand panel for evidence, constraints and comments. Let users compare candidates side by side. Display draft, changes requested and approved states. Provide a hiring-manager preview link with comments anchored to the relevant candidate. Make the task-specific outcome recruiter-approved shortlists linked to evidence visible beside its review state, override history and value baseline.

Accounts and administration

Project ownership, candidate record versions, hiring-manager comments, approval states, sourcing allowances, assessment limits, export history and a rights record for supplied candidate data. 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, calendar and scheduling tools, Slack, assessment providers and authorized sourcing channels. Start with file exchange and validate destination specifications before promising direct ATS 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: source candidates from authorized channels; screen and evaluate candidate profiles. 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

   10 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 recruiters and hiring managers filling repeated role types use it to solve "candidate sourcing, screening and scheduling are split across several tools, and match decisions cannot be explained or overridden"?
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 interview.
4. Measure, then decide. Track accepted shortlists per recruiter hour and corrections after interview; 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 authorized sourcing channels; final hiring decisions and employment terms remain human. Implement one approved input format, a bounded representative case set and the first two task modules: source candidates from authorized channels; screen and evaluate candidate profiles. Support the third module with operator review: match candidates to role requirements and preferences. 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 role families and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around recruiter-approved shortlists linked to evidence. Retain the explicit scope boundary: One fixed role family and authorized sourcing channels; final hiring decisions and employment terms remain human.

What the build depends on. Candidate data upload and preview, asynchronous sourcing and assessment jobs, editable version history, reviewer access and tested export formats. High-fidelity hiring requires qualified human review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed role family and authorized sourcing channels; final hiring decisions and employment terms 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 family. Offer a monthly sourcing and screening allowance after repeat demand. Quote complex multi-region or executive search separately. These are test prices, not market benchmarks. Package the initial sale as one bounded recruiter-approved shortlist linked to evidence. Recurring fees must specify role volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-placement 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 manual screening and coordination while keeping every match decision explainable and recruiter-approved. Demonstrate a concrete recruiter-approved shortlist linked to evidence using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Recruiters and hiring managers filling repeated role types professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample recruiter-approved shortlist linked to evidence from a small authorized input set, with a transparent calculation of accepted shortlists per recruiter hour and corrections after interview and no promised savings.

The first 30 days

1. Week 1: interview five recruiters and hiring managers filling repeated role types and inspect a recent example of candidate sourcing, screening and scheduling split across several tools with unexplainable match decisions.
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 interview, 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 interview. 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 shortlists per recruiter hour and corrections after interview; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs recruiter-approved shortlists linked to evidence. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased role 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, sourcing constraints and review examples, together with reliable delivery for a narrow hiring niche. Build a permissioned library of representative role cases, recruiter corrections and verified operating constraints for recruiters and hiring managers filling repeated role types. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

ClousH Demo, Contrario, Donna AI, Holly, Roster, Bolto, job boards, staffing agencies and manual spreadsheet screening. Compare this product with the buyer's present method on accepted shortlists per recruiter hour and corrections after interview. Offer a bounded paid workflow instead of claiming broad autonomous hiring expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Sourcing and assessment attempts, data storage, reviewer hours, client revision rounds and licensed candidate data sources. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of recruiter-approved shortlists linked to evidence. Track cost per accepted shortlist, including correction work, unsuccessful cases and support.

Preserve candidate privacy, source attribution, evidence accuracy and data permissions. Recruiters approve substantive match decisions and hiring scope. One fixed role family and authorized sourcing channels; final hiring decisions and employment terms remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.