Hiring coordination and candidate screening portal

For

Recruiting teams and hiring managers handling screening, interviewing and candidate management

Solves

Hiring tasks are split across several subscriptions, so candidate data, interview notes and decisions live in disconnected tools.

Delivers

Reviewer-approved candidate shortlists and interview records

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

Reduce tool sprawl and manual coordination while keeping hiring decisions with the employer.

1. Track candidates from application to hire with status updates and notes.
2. Parse resumes and extract candidate information.
3. Rank or filter candidates by fit to job requirements.
4. Run AI screening interviews with generated questions and grading.
5. Provide interview simulations with generated questions and feedback.
6. Send automated candidate emails.
7. Post job openings across multiple channels.
8. Generate job descriptions from role requirements.
9. Give real-time feedback as users write or interview.
10. Check grammar, spelling and style.
11. Coordinate hiring-team feedback and decisions.
12. Show dashboards and reports on recruitment metrics.
13. Organize, assign and track tasks with deadlines.
14. Set automation rules to reduce manual work.
15. Support team chat and messaging.
16. Store and share documents and media securely.
17. Capture interview insights with AI note-taking and analytics.
18. Run background checks and manage references.
19. Compare the reviewed result with the recorded baseline and value assumptions.
20. Capture corrections and named-owner approval before consequential use.
21. Export a versioned reviewer-approved candidate shortlist and interview record with source references and unresolved questions.

Everything these tools do, in one app

• Applicant Tracking Manage candidates from application to hire with status updates and notes.Found in KaziQuest e-Recruiting Software, Screenloop
• Resume Parsing Automatically extract candidate information from resumes.Found in KaziQuest e-Recruiting Software, CandiView
• Candidate Matching Rank or filter candidates by fit to job requirements.Found in Braintrust AIR, Spott, AgentR 2.0
• AI Screening Interviews Conduct screening interviews with AI-generated questions and grading.Found in Braintrust AIR, AgentR 2.0
• Interview Simulations Practice interviews with AI-generated questions and receive feedback.Found in Intrvuz, Braintrust AIR
• Automated Candidate Communication Send automated emails to candidates.Found in KaziQuest e-Recruiting Software
• Job Posting Management Post job openings across multiple channels.Found in KaziQuest e-Recruiting Software
• AI Job Description Generation Generate job descriptions based on role requirements.Found in Braintrust AIR
• Real-Time Feedback Provide immediate feedback as users write or interview.Found in Perfect, uBest, Braintrust AIR and 1 more
• Grammar and Style Checking Identify and fix grammar, spelling, and style issues.Found in Perfect, uBest
• Team Collaboration Enable hiring teams to coordinate feedback and decisions.Found in AgentR 2.0, KaziQuest e-Recruiting Software, MyKaya
• Reporting and Analytics Provide dashboards and reports on recruitment metrics.Found in KaziQuest e-Recruiting Software, AgentR 2.0, Screenloop and 1 more
• Task Management Organize, assign, and track tasks with deadlines.Found in MyKaya
• Automated Workflows Set up automation rules to reduce manual work.Found in MyKaya
• Team Communication Facilitate quick information exchange via chat and messaging.Found in MyKaya
• File Sharing Securely store and share documents and media.Found in MyKaya
• Interview Intelligence Capture interview insights with AI note-taking and analytics.Found in Screenloop
• Background Checks and References Perform background checks and manage references.Found in Screenloop

What goes in, what comes out

The workflow

1. In
   Start with

   Job requirements, resumes, interview notes and hiring rules

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect job requirements

4. 3

   Resumes

5. 4

   Interview notes and hiring rules

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewer-approved candidate shortlists and interview records

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate rankings, screening questions and draft communications 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. One hiring workflow and one approved question set; final hiring decisions and adverse-action checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Role and requirements setup, Candidate pipeline, Interview and review workspace. Use a pipeline board for candidates, a central candidate record with resume, screening answers and notes, and a right-hand panel for team comments, tasks and decisions. Let users compare candidates side by side. Display applied, screening, interview, offer and rejected states. Provide a hiring-manager review link with comments anchored to the relevant candidate record. Make the task-specific outcome reviewer-approved candidate shortlists and interview records visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, candidate record versions, team 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

Employer-owned job boards, email systems and HRIS records. Cloud document storage, calendar and messaging destinations. Start with file exchange and validate destination specifications before promising direct publishing. 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

   6 days

   One buyer segment, one recurring use case; first modules: track candidates from application to hire with status updates and notes; parse resumes and extract candidate information. 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 recruiting teams and hiring managers handling screening, interviewing and candidate management use it to solve "hiring tasks are split across several subscriptions, so candidate data, interview notes and decisions live in disconnected tools"?
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: Time from application to shortlist and reviewer corrections per candidate.
4. Measure, then decide. Track time from application to shortlist and reviewer corrections per candidate; 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 hiring workflow and one approved question set; final hiring decisions and adverse-action checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: track candidates from application to hire with status updates and notes; parse resumes and extract candidate information. Support the third module with operator review: rank or filter candidates by fit to job requirements. 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 candidate shortlists and interview records. Retain the explicit scope boundary: One hiring workflow and one approved question set; final hiring decisions and adverse-action checks remain human.

What the build depends on. Candidate upload and preview, asynchronous screening jobs, editable version history, reviewer access and tested export formats. High-fidelity hiring support requires specialist HR QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One hiring workflow and one approved question set; final hiring decisions and adverse-action checks 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 hiring workflow. Offer a monthly production allowance after repeat demand. Quote complex integrations or specialist screening separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewer-approved candidate shortlist and interview record. 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 tool sprawl and manual coordination while keeping hiring decisions with the employer. Demonstrate a concrete reviewer-approved candidate shortlist and interview record using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Recruiting teams and hiring managers 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 candidate shortlist and interview record from a small authorized input set, with a transparent calculation of time from application to shortlist and reviewer corrections per candidate and no promised savings.

The first 30 days

1. Week 1: interview five recruiting teams and hiring managers handling screening, interviewing and candidate management and inspect a recent example of hiring tasks split across several subscriptions, so candidate data, interview notes and decisions live in disconnected 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 time from application to shortlist and reviewer corrections per candidate, 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: Time from application to shortlist and reviewer corrections per candidate. 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

Time from application to shortlist and reviewer corrections per candidate; 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 candidate shortlists and interview records. 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 screening questions, hiring constraints and review examples, together with reliable delivery for a narrow hiring niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for recruiting teams and hiring managers handling screening, interviewing and candidate management. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Braintrust AIR, KaziQuest e-Recruiting Software, Perfect, AgentR 2.0, uBest, Spott, MyKaya, Screenloop, CandiView and Intrvuz. Compare this product with the buyer's present method on time from application to shortlist and reviewer corrections per candidate. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, resume parsing, storage, reviewer hours, client revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewer-approved candidate shortlists and interview records. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve candidate privacy, source attribution, screening accuracy and usage permissions. Employers approve substantive changes and hiring scope. One hiring workflow and one approved question set; final hiring decisions and adverse-action checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.