Every recruiting professional has been there—staring at a resume where someone claims they “drove 3x company growth” at their last three positions. But did they really? Or were they just lucky enough to ride the wave at rapidly scaling companies during boom periods?
Last week, I had the opportunity to meet with Liv Anderman, VP at Findem, to understand how their “3D data” approach tackles this exact problem. What emerged from our conversation was a platform that goes far beyond traditional recruiting tools by combining self-reported candidate data, company context and timeline information to create what might be the most comprehensive candidate profiles I’ve encountered in talent acquisition technology.
The State of Play: Why Resume-Based Recruiting Is Breaking Down
The fundamental challenge facing talent acquisition teams today isn’t just volume—it’s data quality and authenticity. Resumes represent perhaps the most unreliable dataset ever, yet organizations use them for critical business decisions every day. They’re self-reported, subjective, and often written to optimize for keyword matching rather than accurate representation.
This problem has intensified dramatically with AI tools enabling candidates to rapidly customize resumes and apply to hundreds of positions daily, regardless of actual fit. Recruiters now face an unprecedented volume of applications, many from candidates who’ve never read the job description. Even more concerning is the rise of fraudulent applications—fake profiles, misrepresented credentials, and entirely fabricated work histories that can slip through initial screening processes.
This data problem becomes acute when combined with mounting business pressures. Talent leaders need to demonstrate measurable business impact while recruiters face efficiency demands and the ongoing challenge of identifying genuine talent among a sea of applications—many of which may not be authentic. The result is a system where everyone is working harder but not necessarily smarter.
How the Market Is Responding: Five Distinct Approaches
The talent acquisition technology landscape has fragmented into several distinct camps, each addressing these challenges differently:
Eightfold AI operates as a talent intelligence platform that combines AI-powered candidate sourcing, internal mobility tools, and workforce development capabilities. The platform uses deep learning to analyze skills and potential rather than traditional resume-based matching, covering both talent acquisition and employee development with features like succession planning and personalized career pathing.
HireVue focuses on assessment-driven hiring through AI-powered video interviews and screening tools. The platform enables structured, on-demand video interviews with behavioral analysis and pre-employment evaluations, designed primarily for organizations managing high-volume hiring processes.
Paradox delivers conversational AI through their chatbot “Olivia” that handles initial candidate interactions, screening, and scheduling. The platform automates standard recruiting tasks like interview coordination and basic qualification screening, with proven implementations at companies like General Motors.
SeekOut operates as an AI-powered talent sourcing platform that aggregates over 750 million candidate profiles from various public sources including LinkedIn, GitHub, and research databases. The platform specializes in finding hard-to-reach talent and offers advanced diversity recruiting capabilities through demographic filtering.
Braintrust AIR provides automated sourcing and screening through AI-conducted video interviews that generate instant scorecards and recommendations. The platform also include AI-powered job description generation, candidate matching from their network, and automated video interviewing with scoring capabilities.
What Makes Findem’s Approach Different
Where Findem diverges from this landscape is in their foundational data strategy. Rather than starting with resumes or relying on candidates to self-report through AI interviews, they’ve built what they call “3D profiles” by combining:
People Data + Company Data + Timeline Context
This means when you see someone’s experience at Microsoft, you’re not just seeing their title and tenure—you’re seeing the company’s headcount growth, financial performance, and product releases during their specific time there. If someone was at a startup during a Series B funding round, or at a public company during a major acquisition, that context becomes part of their profile.
The practical implications are significant:
- Verified Career Trajectories: Rather than taking someone’s word that they have “startup experience,” the platform can identify candidates who’ve been at companies during specific growth phases—Series A scaling, post-IPO transitions, or turnaround situations
- Data-Driven Attributes: Custom attributes can be built for organizational needs. If you’re an animal rights organization looking for “mission-driven” candidates, Findem can create filters based on involvement with relevant charities or causes
- Comprehensive Talent Ecosystem: The platform consolidates external sourcing, internal mobility, referrals, past applicants, and inbound candidates into unified workflows rather than treating them as separate channels
Does This Sound Like Your Organization?
While advanced data capabilities can benefit many organizations, Findem’s approach creates particularly compelling value in these scenarios:
Mid-Market Companies Scaling Rapidly
- Need to make precise hires where cultural and experiential fit matters enormously
- Benefit from consolidated workflows that reduce tool sprawl
- Require data-driven insights to compete for talent against larger organizations
Enterprise Organizations in Competitive Industries
- Technology, consulting, and financial services where battle-tested experience is crucial
- Companies making significant investments in AI strategy who need the best possible talent data
- Organizations with complex internal mobility needs requiring sophisticated matching
Companies Prioritizing Diversity and Inclusion
- Probabilistic diversity insights help teams understand talent pool demographics
- Data can reveal hidden talent pools and prevent over-reliance on traditional sourcing channels
- Analytics help identify when requirements might inadvertently limit diverse candidate pools
Executive Search and Strategic Roles
- Senior positions where specific growth-stage experience is a differentiating factor
- Roles requiring proven experience navigating particular business challenges
- Situations where traditional executive search methods need augmentation with broader data
The Strategic Shift: From Reactive to Proactive Talent Strategy
The most compelling aspect of Findem’s positioning is their emphasis on enabling proactive talent strategies. Much like marketing teams have evolved from reactive campaign management to predictive customer intelligence, talent acquisition is beginning to move in a similar direction.
The platform’s market intelligence capabilities allow talent leaders to understand competitor hiring patterns, identify talent movement trends, and build more strategic talent pipelines. One customer used these insights to discover they were consistently losing AI talent to first-tier companies while recruiting from second-tier firms—a wake-up call about their market positioning.
This strategic layer transforms recruiting from a transactional function to a business intelligence capability. When talent leaders can walk into executive meetings with data about competitor strategies, market dynamics, and precise talent availability, they shift from order-takers to strategic advisors.
Looking Forward: Solving a Fundamental Information Problem
Reflecting on our conversation, Findem is tackling something much more fundamental than technology upgrades—they’re addressing an information problem that has plagued hiring since the beginning of time. The challenge of truly knowing who someone is professionally, what they’ve accomplished, and what experiences have shaped them has always been at the heart of good hiring decisions.
What’s changed is our ability to solve this problem in real-time using advanced AI and data tools. Rather than accepting the limitations of self-reported resumes or relying on time-intensive reference checks, platforms like Findem are making comprehensive candidate intelligence accessible at scale.
The talent acquisition market is clearly moving toward more sophisticated data utilization and AI integration. Organizations that embrace these comprehensive candidate intelligence solutions now may find themselves with significant competitive advantages as the war for talent intensifies.
For companies ready to tackle the fundamental information problem in hiring, platforms like Findem represent a compelling solution to challenges that have existed for decades. For others, the simpler automation and engagement tools may provide better immediate value. The key is understanding which approach aligns with your organization’s hiring challenges—and investing accordingly.
