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Today we’re releasing HiPeople AI Resume Screening. It’s built to help top talent acquisition teams screen high volumes of applicants quickly, consistently, and in line with global compliance frameworks.
Let’s start with two quotes we picked up during conversations with TA leads over the last 12 months at meetups around the world.
I just got 300+ applicants in 3 days. I’ll randomly pick a few to screen. (Corporate recruiter, 5,000+ FTE restaurant chain)
I always reject people from this university. My ex went there and I hate those people. (VP of TA, 1,000+ FTE tech company)
While humans often worry about bias from AI, the reality is: bias from humans far outweighs it. And even if we had a fully objective recruiter screening hundreds of resumes, consistency would still be nearly impossible. Give the same resume to the same recruiter on a different day and you’ll likely get a different result. And that’s fine. We’re human. Our decisions are affected by our fitness, sleep, emotions, stress levels, and even what we ate for breakfast.
Meanwhile, most candidates put a lot of effort, hope, and ambition into their applications. They dream of a better job, a better team, and more exciting challenges to solve. Yes, also more money. Marketers like Google label job changes as life events. So applications carry a lot of weight for candidates. Unfortunately, many are not even looked at, or if they are, it’s through highly manual and biased techniques.
That’s not just inefficient. It’s inhumane. Every applicant, every human putting together an application, deserves to be seen (excluding the ones who just spam using multi-application tools, ok!). That’s what HR and TA are about.
TA teams are overwhelmed. With fewer open jobs and many more people looking for work, most TA teams we speak to daily are seeing all-time high application volumes. We believe that application volumes will likely increase over the next 12 months and beyond due to several reasons:
Many companies (see Shopify or Spotify) have rolled out a new modus operandi across their orgs, making AI essential. This shift also affects TA at those companies today and at all companies soon.
AI has reached the maturity to deliver real value to TA teams today. Dave Owen expects resume screening to be 90% automated with AI. And that’s a good thing. We’ll see better screening decisions, fairer outcomes (less bias, more inclusion), dramatically faster time to first interview and hire, lower cost-of-hire, and for the first time, every applicant given a real chance as soon as they enter your ATS.
First, connect your ATS. HiPeople continuously syncs all job data (active candidates, hiring teams, job descriptions) with HiPeople, keeping both systems perfectly in sync.
Hiring teams set up their jobs by:
1. Defining screening criteria. Teams can use AI-generated prompts as is, edit them, delete them, or create their own. (Wondering how to write great prompts? See our doc on Writing clear prompts)
2/ (Optional) Setting a screening limit for calibration runs and to manage credit usage.
3/ Setting workflows. Connect HiPeople AI Resume Screening to the right ATS stage, and define auto-rejection and auto-advance rules. Rejection reasons and advancement can sync bi-directionally with your ATS.
Once set up, recruiters can click "screen" and see results in an easy-to-consume candidate table with filters for high, medium, and low matches. They can sort by application date, score, criteria match, and more.
When diving into a candidate, recruiters see the original resume alongside a match breakdown with clear, factual evidence behind each score. HiPeople explains its judgment and quotes the specific resume sections that led to it.
Which TA team has that level of documentation for manual screening?
We spoke with dozens of top TA teams from tech, consumer, healthcare, energy, and more. The result: a product that understands resumes like a recruiter. This goes far beyond keyword matching, which can confuse Java with JavaScript or flag "English" because someone likes English tea.
HiPeople AI Resume Screening uses leading LLMs to interpret resumes contextually. Take Sundar Pichai's LinkedIn profile: it doesn’t list keywords like "CEO responsibilities," but human recruiters know he qualifies as a global tech CEO. HiPeople does too.
Anyone can quickly build a resume tool with Lovable or Bolt. But it won’t yield consistent, valid, and reliable results that TA teams need to spot top talent and stay compliant. We rooted our product in I/O psychology and spent months ensuring it delivers repeatable outcomes.
We anonymize resumes and apply pre-processing steps to minimize bias in AI evaluations.
We offer native ATS integrations with deep functionality:
Supported ATS (reach out if yours is missing):
We invested months, developing safeguards to detect AI-enhanced resumes or attempts to game the system with tactics like keyword stuffing in small font sizes.
We already see tremendous value delivered to TA teams globally. But we’re just getting started. Alongside weekly enhancements, two major features are launching in H2 2025:
Automatically find great candidates for other open roles.
Enrich company names in resumes with background data so you instantly know what "Intersect Technology" is.
We built HiPeople for responsible AI from day one.
We evaluate only the skills, experience, and criteria that TA teams define. We ignore age, gender, names, graduation dates, and other proxies for bias.
By default, we don’t train the model on your past decisions. Each resume is screened as a clean slate.
Every release undergoes bias simulations across diverse datasets. It’s built into our QA process.
We are certifying compliance with NYC Local Law 144, Colorado SB205, the EU AI Act (once finalized), and more. Reach out to your CSM or contact sales for specifics.
HiPeople AI Resume Screening is now available to all customers on HiPeople credit plans. Credit consumption follows your current scheme. To start, reach out to your CSM or contact sales.