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Harver

HR
Velocity5.0

Talent assessment platform automating high-volume hiring with AI-driven assessments

harver.com ↗

Harver's public feed is a hiring-science content program, not a product changelog.

skills-based hiringai readinessassessment validitytalent analyticsretentioncontent marketing
◆Current state
Everything Harver publishes on this feed is long-form thought leadership about assessment science — validity, adverse-impact defensibility, and what actually predicts job performance — much of it bylined to in-house I/O psychologists. There are no release notes, version numbers, or feature announcements in the visible stream. Product capability can only be inferred second-hand, through the assessment concepts the posts argue for.
◆Where it's heading
The editorial line has consolidated around a single claim: organizations are hiring for AI-era work without any measurement of whether their people can adapt. Three of the last ten posts build out 'AI readiness' as a construct that ought to be tested rather than assumed, and a parallel thread argues that validated assessments are what survives legal and executive scrutiny. Customer proof points like the Pandora case study are being used to attach dollar figures to that argument.
◆Prediction
Expect more AI-readiness material aimed at internal mobility and redeployment rather than external hiring alone, plus additional named-customer outcome stories. Nothing in this feed indicates what Harver is actually shipping, so no product move can be predicted from it.

◆Recent moves

  1. 11d ago

    Why Customer Service Teams Can’t Afford to Skip Written English Screening

    A marketing post arguing that customer-service hiring should screen written English directly instead of inferring it from resumes. It narrows the general assessment-validity thesis to one role family; no product capability is described.

    View source ↗
  2. 15d ago

    How Pandora Cut Attrition 25% and Unlocked $35M With Assessments

    A customer case study claiming Pandora cut time-to-hire from 38 to 15 days and attributed $35M in sales value to predictive assessments. It supplies the outcome numbers the surrounding thought-leadership thread otherwise argues in the abstract, but it is sales collateral rather than a release.

    View source ↗
  3. 2mo ago

    Defensible Hiring: How Validated Assessments Hold Up Under Scrutiny

    An argument that validated assessments hold up better than resumes or unstructured interviews when hiring decisions are challenged. This is the defensibility half of Harver's editorial position, aimed at buyers worried about scrutiny rather than speed.

    View source ↗
  4. 2mo ago

    You’re Hiring for AI Readiness. You Have No Idea If Your Current Workforce Has It.

    Positions AI readiness as a measurement gap that spans the whole talent lifecycle, not just new hires — organizations cannot say whether existing staff can adapt or be redeployed. It is the clearest statement of the theme the recent feed keeps returning to.

    View source ↗
  5. 2mo ago

    Why 55% of Employers Now Regret AI-Driven Layoffs

    Uses a 55% employer-regret statistic on AI-driven layoffs to argue that workforce cuts are being made without evidence about what people can do. Same AI-readiness thesis as the surrounding posts, framed through the cost of getting it wrong.

    View source ↗
  6. 3mo ago

    The Science Behind Skills-Based Hiring: What Predicts Performance and How to Measure It

    A foundational explainer on what predicts job performance and how to measure it, pitched at both executive and talent-leader audiences. It is the evergreen base the newer AI-readiness posts build on top of.

    View source ↗