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Metaview’s Application Review helps you handle high volumes of inbound applications by assessing candidates against your role requirements in a structured, consistent way while keeping you in control of every decision. It was developed in partnership with recruiting teams at leading companies, and is designed to fit into your existing hiring workflows rather than replace them.

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What Application Review does — and doesn’t do

Application Review helps to classify and summarizes. It doesn’t decide.
  • You define what “good” looks like for the role through an Ideal Candidate Profile (ICP)
  • Each application is analyzed individually against your ICP and assigned a match category with written reasoning
  • You review the outputs and make every decision
Nothing happens automatically. Application Review does not progress or reject candidates. A match category on its own has no effect on the candidate’s application and changes only sync back to your ATS when you explicitly update a candidate’s status yourself.
Each application is assessed individually against your ICP. There is no ranking, no curve, and no comparison between candidates — a match category reflects how well that application aligns with your criteria, regardless of who else has applied.

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How it works

  1. Define your ICP. Select a role from your ATS and attach a job description if available. Metaview generates a draft ICP covering must-have criteria, nice-to-haves, and role context. Review and edit this before classification begins.
  2. AI analyzes applications. Each application is evaluated individually against your approved ICP, using only the materials in your ATS. No external data is used.
  3. Candidates are grouped with reasoning. Each candidate receives a match category and a written explanation of how their application was assessed.
  4. You review and decide. You decide who to look at more closely, who to interview, and who to progress or decline.
If an application comes back as Inconclusive, the CV was missing, corrupted, or couldn’t be parsed. It’s not a quality judgment.

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Setting up your ICP

The quality of outputs depends directly on the quality of your ICP. Vague criteria produce less consistent results.
  • Be explicit about must-haves vs. nice-to-haves. Separate what’s genuinely essential from what would strengthen a candidacy.
  • Anchor to the job, not intuition. Focus on skills, experience, and outcomes directly relevant to the role.
  • Use clear, specific language. “3+ years in B2B SaaS customer success” is more useful than “customer success experience.”
  • Avoid criteria that could introduce bias. Stick to skills, experience, and role-relevant outcomes. Criteria that reference personal characteristics or signals unrelated to job performance can lead to unfair outcomes, so it’s worth reviewing your ICP with this in mind before classification begins.
  • Calibrate early. Match categories aren’t permanent — they reflect the current ICP. When you update your ICP, all applications are reclassified accordingly. This means it’s worth calibrating early: review a few candidates from each match category, check whether the classifications feel right, and refine your ICP before working through the full pipeline.
If your team is sharing a pipeline, agree on the ICP together before you start — and compare notes on borderline cases as you go.

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Reviewing outputs and making decisions

When you start reviewing applications, where do you begin? Most recent first? Earliest first? A keyword or ATS filter? Application Review gives you another way by grouping applicants into match categories based on your ICP. Every classification comes with reasoning, so you can see how it was assessed and check it against the actual application. Keep in mind that match categories reflect alignment with your ICP, not the quality of the candidate so a strong candidate with a sparse resume may end up as a lower match simply because the application didn’t surface enough evidence against your criteria. Classifications can vary with the clarity of your ICP and the completeness of the application materials. You can always review the full application, filter or sort using other parameters, and of course you’ll make your own decision on every candidate.

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Keeping things fair

Application Review is designed to support fairer, more consistent evaluation by structuring how applications are assessed and applying the same criteria across every candidate. It does not use protected characteristics in its analysis, and we run both internal and independent third-party testing to help ensure reliable performance. Beyond that, the same good practices you’d follow in any part of your hiring process apply here too: ground your ICP in job-relevant skills and experience, apply consistent standards across candidates, and check in on outcomes periodically to make sure things are tracking the way you’d expect. As with any hiring tool, it helps to make sure your team using Application Review is familiar with your company’s policies and any applicable local requirements.

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Your responsibilities

A few practical steps sit with you as the employer. Requirements vary by jurisdiction, so check with your legal team on specifics.
  • Transparency. Some jurisdictions require that applicants are informed when AI is used as art of your hiring process. A short note in your privacy policy, job posting, or application portal is usually sufficient.
  • Offer an opt-out where required. Some jurisdictions give candidates the right to opt out of AI-assisted processing. This is built into the platform, so you need to make sure candidates know it’s available.
  • Handle data subject requests. Candidate data originates from your ATS therefore if a candidate requests access to or deletion of their data, that obligation sits with you. Metaview provides the tools to support this.

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Data and privacy

Application Review only uses applicant personal data from your ATS and it is not enrich or supplemented from external sources. In some cases, Metaview may enrich contextual information about organisations or institutions (such as a company’s industry or size) using third-party data sources. “This information is used solely to support UI features within the platform — such as displaying company profiles, logos, and related metadata — and plays no role in applicant evaluation. It does not add new personal data about the applicant Your data is never used to train AI models, is not shared across customers, and is not used to generate or improve results for other customers. For more detail on data processing, AI governance, bias testing, and security, please refer to our Trust Center, where we provide documentation including our SOC 2 Type II report and independent bias testing report. If you have any additional questions, you can reach us at privacy@metaview.ai.

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You’re in control

Application Review helps you move faster by structuring and summarizing candidate information — but every decision remains yours. The AI supports your workflow; you decide who to review, who to progress, and who to hire. If you have questions or need help getting started, our team is here to support you.