What is the best AI candidate scoring tool for recruiters?
For recruiting agencies and in-house teams that want scores inside their recruiting workspace, Mainder is our pick. It scores every candidate against the role requirements, your company values and your past hires, returns a match percentage with the reasons behind it and never rejects anyone on a score: the only automatic rejection is a knockout question your team set up. If you already run Greenhouse or Workable, their built-in scoring is the shortest path. If you want to keep your ATS and add a scoring layer, look at Eightfold or hireEZ.
Where the seven differ most is who acts on the score. Greenhouse, Manatal, Eightfold, hireEZ and HireVue say the decision stays with people. Workable and Mainder can both reject automatically, but only on criteria your team sets: Workable when auto-disqualify is turned on for a job, Mainder when a candidate fails a knockout question.
This guide is written by Mai for Mainder, so Mainder comes first. Every statement about the other tools comes from the vendor's own website, help center, trust pages or published audit reports, checked on 15 October 2026. We left out prices, which change often, and we only describe what each vendor says about itself.
AI candidate scoring tools compared
| Tool | Best for | What it scores | Explanation and control | Who decides | Where it runs |
|---|---|---|---|---|---|
| Mainder | Agencies and in-house teams that want scoring, sourcing and the ATS in one place | Role requirements, company values and past hires, as a match percentage | Reasons for each score; criteria you can correct | Your team. Only knockout questions reject automatically | Built-in ATS; connects with Greenhouse, Lever and Ashby |
| Greenhouse | Companies that run structured hiring | CV against recruiter-defined calibrations, in five match categories | Matched skills and reasoning; customizable calibrations | The hiring team; no auto-reject or auto-advance | Its own ATS |
| Workable | Teams with hundreds of applicants per role | CV, profile and answers against an ideal profile, out of 100 | Reasoning for every score | Can auto-disqualify if enabled for a job | Its own ATS |
| Manatal | Agencies that want an ATS with AI matching on their own candidate database | Your database against requirements read from the job | Line-by-line reasons; weights you can set | The recruiter | Its own ATS |
| Eightfold AI | Large enterprises on Workday, SAP or Oracle | Job fit from titles, experience, education and skills, 0 to 5 | Breakdown of skill, experience and title relevance; scores reflect calibrated job requirements | People; it does not reject or advance on its own | On top of your ATS or HR system |
| hireEZ | TA teams that want to rank applicants without changing ATS | Résumé and application against the job, in four match labels | Personas you can fine-tune | The user; rejection is manual | Its own platform, or alongside 50+ ATS |
| HireVue | Enterprise and high-volume hiring with structured interviews | Interview answers and assessments against job competencies | Scores tied to behavioural anchors; competency weighting | Recruiters make the final call | Connects to Workday, SAP, Oracle and others |
Mainder: scoring inside the recruiting workspace
Mainder AI Scoring ranks every candidate before anyone opens a profile. It compares each person with the requirements of the role, such as stack, seniority and location, with your company values and with your past hires, and gives a match percentage. Every candidate for a role is scored against the same criteria, so the first screen no longer depends on who does it or on which day. For an agency, that also means the reason behind every name on a shortlist can be explained to the client.
What it does:
- Records every score with its reasoning: which signals push it up, which pull it down and how confident the model is. If a score surprises you, you can see which criteria produced it and correct them.
- Learns from your hiring decisions and client feedback, and gets sharper with every placement you close.
- Cuts time to shortlist by around four times, because the strongest candidates in your database surface before anyone reviews them by hand.
- Never rejects anyone on a score. The only automatic rejection is a candidate who fails a knockout question your team set up.
Scoring sits in the same workspace as sourcing, outreach and the ATS. Top-scored candidates can go straight to an AI screening interview, and each score stays attached to the candidate as they move through the pipeline. Mainder operates under GDPR, holds ISO 27001:2022, runs impact assessments for high-risk AI features and documents controls aligned with the EU AI Act. Your data is never used to train AI models, and more than 300 recruiting teams use the platform.
Best for: agencies and in-house teams that want explainable scoring, sourcing and the ATS in one place, especially in Europe and Latin America.
Greenhouse
Greenhouse adds AI scoring to its ATS through Talent Matching, part of its Real Talent offering. The AI reads each résumé, compares it with calibration criteria the recruiter defines and places the candidate in one of five categories, from "Strong match" to "Needs manual review". You can see which skills matched, and an export includes the category with its reasoning.
Greenhouse states that Talent Matching "does not auto-reject or auto-advance any candidate" and that disposition decisions stay with the hiring team. It says its AI recruiting aligns with NYC Local Law 144, Colorado SB 205, the EU AI Act and California FEHA, runs monthly third-party bias audits with Warden AI and holds ISO 42001:2023.
Best for: companies that already run structured hiring in Greenhouse.
Workable
Workable's Screening Agent evaluates every candidate against an ideal candidate profile and assigns a score out of 100, using the CV, the profile and the answers to application questions. Workable says protected characteristics are excluded by design and that every score comes with reasoning. Its help center states that must-have criteria count twice as much as the rest.
Like Mainder's knockout questions, its automatic disqualification acts only on criteria your team marks as disqualifying: it can be turned on or off for each job, and when it is off, unmet criteria are only highlighted. Workable says its agent is aligned with the EU AI Act and lists ISO 27001, ISO 27017 and SOC 2 Type II. It hosts data in the AWS US East region.
Best for: small and mid-sized teams that receive hundreds of applications per role and want to filter the obvious no's.
Manatal
Manatal is an ATS and CRM for recruitment agencies and HR teams. Its AI recommendations read the intent of a job (skills, experience, education and location) and return a ranked shortlist from your own candidate database. Each match comes with line-by-line reasons. Required criteria count for more than preferred ones, and you can turn on weights to set how much each criterion counts.
Manatal says its AI is meant "to guide, not replace" your judgment and that final decisions remain yours. It mentions GDPR, CCPA and PDPA compliance and SOC 2 Type II, and states that customer data is stored in the USA. Its security and AI feature pages do not mention the EU AI Act or bias audits.
Best for: agencies that want an ATS with AI matching on their own candidate database.
Eightfold AI
Eightfold is a talent intelligence platform that sits on top of an existing ATS or HR system. Its model predicts how well a candidate matches a job from titles, experience, education and skills, on a scale from 0 to 5, and shows a breakdown of how the candidate's skills, experience and job titles match the role. Eightfold says its match score reflects the customer's calibrated job requirements.
Eightfold states that its software does not reject a candidate or advance anyone through a hiring stage on its own. It publishes independent bias audits under NYC Local Law 144, runs a compliance program for the EU AI Act, holds ISO 42001 and offers regional data residency on AWS.
Best for: large enterprises on Workday, SAP SuccessFactors or Oracle.
hireEZ
hireEZ is a recruiting platform that covers sourcing, CRM and its own ATS. Its Applicant Review compares each applicant's résumé and application with the job and labels them "Best Match", "Good Match", "Partial Match" or "Not a Match". It only analyses the data the applicant submitted, and users can fine-tune the persona it matches against.
hireEZ states that its AI technologies "do not make any employment decisions", which are always made by its users. hireEZ publishes 2026 independent bias assessments by Armilla AI that follow NYC Local Law 144 and hosts data in AWS US regions. It integrates with more than 50 ATS, including Workday, Greenhouse and Lever.
Best for: talent acquisition teams that want to rank applicants without leaving their current ATS.
HireVue
HireVue scores interview answers and game-based assessments, where the other tools in this guide start from the CV. Its AI evaluates the transcript of each answer against role-specific criteria, ties scores to behavioural anchors and explains them with evidence from the transcript. HireVue says it does not analyse facial expressions or tone of voice, and customers can give more weight to chosen competencies.
HireVue's line is "AI informs. Humans decide": recruiters make the final call and candidates can opt out. It describes itself as a provider under the EU AI Act, reports annual independent fairness audits and acts as a processor under GDPR. It connects to Workday, SAP, Oracle, Greenhouse, iCIMS and other ATS.
Best for: enterprise and high-volume hiring that already uses structured video interviews.
AI candidate scoring and the EU AI Act
Candidate scoring is the textbook high-risk case. Annex III of the AI Act lists AI systems used "to analyse and filter job applications, and to evaluate candidates" as high-risk. Regulation (EU) 2026/1744 moved the start of those obligations to 2 December 2027.
A tool you choose now will probably still be in use by then, so ask each vendor today for its documentation on human oversight, explanations and bias testing. Under the Act, you as the employer are the deployer and keep your own duties, whatever the vendor certifies.
How to test an AI candidate scoring tool on your own roles
A demo shows you the vendor's best example. A better test uses a role you closed in the last few months, where you already know who made the shortlist and who you hired.
Once the vendor has signed a data processing agreement, load that role and its applicants into the trial and let the tool score them. Then check whether the people you shortlisted land near the top, and read the reason the tool gives for the two or three candidates it ranks very differently from you. Sometimes it will have caught something your team missed; sometimes the reason will show criteria you would never use. Change one criterion, score again and see whether the ranking moves the way you expect.
While you are in the trial, look for the setting that rejects candidates automatically and find out whether it is on by default. Then read the vendor's trust or help pages on bias audits, data location and the EU AI Act, which usually say more than the homepage.
If you want scores with reasons inside the same workspace where you source and contact candidates, try Mainder AI Scoring on that closed role.
