Disruptions happen. There is no way around it. One of the best ways to reduce stress for recruiting teams and improve predictability for candidates and customers is to automate high volume screening and coordination so human time is focused where it adds the most value.

Giving candidates the space to show up authentically in the application process not only improves engagement, but also helps recruiter–candidate conversations start in a more productive and meaningful place.

More than half of your candidates are active when your office is closed. Only about 45% of job seekers submit applications during the standard weekday 9-to-5 window. The other 55% are applying during evenings, weekends, or irregular hours when recruiters are offline.

AI screening that's push to start. It is essential that hiring solutions have real flexibility built in, so when it is time to ramp up recruiting efforts, your technology can adapt with you. #AIRecruiting #HRTech #RecruitmentInnovation

When we tailor the application process to the candidate, we see higher completion rates and stronger overall engagement. #Recruiting #TalentAcquisition #AIRecruiting #VoiceAI #HRTech #CandidateExperience

When top-of-funnel work takes less time, recruiters can spend more time where it matters, process improvement, candidate connection, and meaningful feedback. #Hiring #Recruitment #FutureOfWork #AIinHR #PeopleOps

Starting follow-up interviews with great notes and a deeper understanding of the candidate reduces bias and leads to more productive conversations. #AIRecruiting #VoiceAI #HRTech #CandidateExperience

24/7 screening does more than improve convenience. It builds a top-of-funnel process hiring managers can rely on. #Hiring #Recruitment #AlwaysOn #AIinHR #PeopleOps

When it comes to hiring, the resume and technical credentials only tell part of the story. Voice AI screening gives recruiters an early glimpse into these qualities, helping them assess fit and prepare for follow-up interviews. #AIRecruiting #HiringInsights #TalentAcquisition

Resume parsing is the foundation of every ATS filtering tool. So I looked at the benchmarks. The results aren't great. An EMNLP 2025 study in November called ResumeBench tested 24 LLMs on structured resume extraction: 2,500 resumes, 50 templates, 5 languages, real JSON schema scoring (the models are a bit out of date): → GPT-4o struggles with multi-column layouts and cross-lingual structure → Code-specialized models actually perform worse than generalists → JSON mode helps schema compliance but doesn't fix semantic errors → Smaller models collapse nested job histories: merging roles, dropping bullets → Reasoning models performed worse than their base counterparts → Most of the llms use pypdf/pytext which can have issues with pdf resume formats or image based resumes If the parsing is unreliable, every decision on matching, ranking, screening inherits that unreliability. And now, it can become a legal liability after the recent Eightfold class-action lawsuit (using AI to covertly score and rank candidates: scraping social media, location data, and browsing activity without disclosure) I'm also watching Google's new open-source tool LangExtract closely. Different approach: every piece of extracted data maps back to its exact location in the original document, with a visual verification layer. That kind of traceability matters a lot more now especially for resumes. @classet_ai, we've taken a different stance on this entirely. We treat the resume as optional supplemental material vs the source of truth. Our AI-powered phone interviews let candidates give context that a resume never captures: why they left a role, what tools they actually used daily, whether they're open to relocation. The conversation is the core data. On the parsing side, we don't trust any single approach. We blend multiple AI models with traditional parsing engines like Senseloaf to make sure we're not missing structured data. If one model drops a certification or merges two jobs together, another catches it. Resume parsing is not a solved problem. Stop making resume filtering the entire decision.

When early outreach and screening are automated, recruiting teams – and candidates – get time back fast. #AIRecruiting #VoiceAI #HRTech #RecruiterEfficiency

Candidate attrition often happens after they’ve already put in the work. The number one reason job seekers stop a process? Never hearing back from the employer. Roughly 40% of candidates abandon their application because they were met with silence.

AI interviews work best when they are truly conversational and two-way. Here is a Nurse sample from our library. Joy runs 24/7, so candidates can screen anytime, anywhere. #Hiring #Recruiting #TalentAcquisition #AIRecruiting #VoiceAI #HRTech #FutureOfWork

Recruiting has evolved a ton over the last few years. What started as simple automations has now grown into real transformations that are fundamentally changing both recruiter workflows and candidate experiences. #AIRecruiting #HRTech #RecruitmentInnovation

The reality of today’s labor market is defined by speed. Data shows that 88% of candidates spend under one hour researching a role before they decide to apply.

When candidates receive immediate engagement from Joy, Classet’s AI agent, after applying, completion rates increase and follow-up conversations with recruiters are more productive. #Hiring #Recruiting #TalentAcquisition #AIRecruiting #VoiceAI #HRTech #CandidateExperience

2/3 of job seekers report that AI-driven screening feels better than traditional recruiter-led phone screens. Candidates value the immediacy and the elimination of scheduling delays that traditional workflows often create. #AIRecruiting #HiringAutomation #TalentAcquisition

To be effective, AI interviews need to be conversational and two-way, meaning candidates can ask questions and the AI responds to what they share. Here’s an example from our sample library for a Warehouse Associate. #TalentAcquisition #AIRecruiting #VoiceAI #HRTech

In high-volume hiring, speed and consistency make the difference. #AIRecruiting #VoiceAI #HRTech