For nearly two decades, talent acquisition vendors have promised to “find hidden talent.” Most of them meant “find people who aren’t active on LinkedIn.” ProvenBase isn’t playing that game—at least, not anymore.
Following a major product pivot and a surge in enterprise adoption, the AI-powered talent intelligence company is making a bold claim: it has finally cracked deep talent discovery at scale, breaking past the limitations of resume databases and social networks. And now it has recruited one of the most respected sourcing experts in the world to validate that ambition.
ProvenBase today announced that Shally Steckerl, widely considered one of the founding architects of modern talent sourcing, has joined its advisory board. The move arrives at a critical moment for the company: massive growth, Fortune 100 customer wins across healthcare, science, government contracting, and other high-complexity sectors—and a platform that looks fundamentally different from anything mainstream TA tools currently offer.
“Not Just Another Semantic Wrapper”: Why Steckerl’s Backing Matters
In a profession full of hype, Steckerl is famously stingy with praise. Since 1996, he has been dissecting recruiting software with surgeon-level precision. When he says most AI recruiting tools are “semantic search wrappers with good marketing,” the industry usually nods along.
That’s what makes his endorsement striking.
“ProvenBase is different. They’ve actually solved the problem of finding talent in non-traditional sources,” Steckerl said. “This is the deep search capability the industry has needed for decades.”
His point: the best technical, scientific, or specialized talent rarely lives inside the public platforms recruiters rely on. Their track records exist in research journals, patent databases, conference proceedings, government labs, and obscure open-source communities—not in polished LinkedIn profiles.
ProvenBase is effectively building a search engine for that world.
Steckerl’s advisory role will center on product strategy, workflow design, and enterprise deployment—three areas where the market has been begging for guidance as TA teams search for new efficiency under aggressive hiring targets and shrinking budgets.
Cracking the Code on Non-Traditional Talent Signals
The core of ProvenBase’s pitch is its Deep Search Engine, a system built to discover talent outside commercial professional networks. It pulls from 50+ sources, including:
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Academic research databases
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Patent offices
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Technical conference archives
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Open-source repositories
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Government lab publications
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Niche scientific communities
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Specialized technical forums
Traditional talent intelligence platforms—LinkedIn Recruiter, SeekOut, HireEZ—have grown more advanced in semantic search. But their data foundations remain constrained to profiles, resumes, and public web signals. ProvenBase aims to leapfrog that constraint entirely.
CEO Ravi Tandra says this pivot started with customer frustration.
“Our clients needed to find quantum computing researchers, biotech scientists, engineers contributing under pseudonyms. Traditional tools fail these searches,” Tandra said. “We built Deep Search to succeed where others couldn’t.”
This is the industry’s unsolved problem: rare, specialized, or passive talent producing real work—but without a recruiter-friendly digital footprint.
ProvenBase’s AI interprets contextual signals, not keywords. If a candidate’s research describes “genome modification using Cas9 proteins,” Deep Search understands that as equivalent expertise to “CRISPR gene editing”—a connection most Boolean-based systems miss.
It’s not magic; it’s data variety paired with contextual machine learning. But it does solve a problem recruiters have battled for 20 years.
Fortune 100 Validation: Enterprise Scale Without Enterprise Bloat
The biggest proof point for the pivot: new Fortune 100 customers already using the platform for large-scale, high-stakes hiring.
One major healthcare organization—managing services for more than 28 million individuals—explicitly cited ProvenBase’s ability to surface clinical and technical talent from research databases and medical publications as a game changer.
This is a real signal of enterprise readiness. Healthcare, biotech, and government contracting are among the hardest sectors to support at scale due to:
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Complex, credential-driven talent pools
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Rapidly evolving scientific fields
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Strict compliance and verification standards
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Highly specialized role taxonomies
If Deep Search can reliably expand these pipelines, it’s solving a real-world problem—not simply refining search operators.
Feature Breakdown: What Makes Deep Search Different
ProvenBase’s value proposition hinges on a combination of breadth and intelligence. Key capabilities include:
Deep Search Engine
Contextual AI trained across dozens of nontraditional sources and specialized domains.
Advanced Cloning
Pattern-matching based on research trajectories, publication histories, and technical contributions—not just job titles or skills lists.
Search Optimization
Real-time refinement recommendations driven by actual candidate output patterns.
Power Search
A Boolean builder with AI-assisted error detection and syntax enhancement.
Smart Search Bar
Natural-language queries automatically converted into multi-source, cross-domain searches.
Entity Resolution Algorithm
Differentiates between similar names across domains—a critical function when navigating academic and research-focused datasets.
ATS/CRM Integrations
Native integrations for systems of record, allowing Deep Search to function as a discovery layer rather than a parallel process.
The company refreshes source data weekly, which is non-trivial considering the diversity of repositories involved.
Why Timing Matters: TA Teams Are Hitting a Wall
ProvenBase’s momentum isn’t just a product story—it’s a market story.
Talent acquisition leaders across industries are facing a convergence of pressures:
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Time-to-hire expectations are rising
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Budgets are shrinking
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Specialized roles are harder to fill than ever
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LinkedIn dependency is reaching a breaking point
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AI regulations will demand better data transparency
In this environment, incremental improvements are insufficient. TA teams need new surfaces of talent visibility, not just better filters on the same pool.
Steckerl put it bluntly:
“Recruiting teams are under siege. Incremental improvements don’t cut it anymore. ProvenBase offers the kind of transformational capability the industry has been waiting for.”
This is the underlying story: a market saturated with “AI for recruiting” tools, but starved for platforms that actually expand the talent universe instead of rearranging it.
Strategic Roadmap: More Data, More Science, More Partnerships
ProvenBase plans to:
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Double its engineering team
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Increase coverage of niche and global talent data sources
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Form partnerships with research institutions and technical communities
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Expand enterprise-scale deployments
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Continue refining contextual AI for scientific and technical domains
If executed well, this positions ProvenBase not just as a sourcing tool but as a legitimate talent intelligence infrastructure layer—a category a handful of vendors have been wrestling to define.
Today, deep talent discovery is a differentiator. In the next two to three years, it could become the minimum operating threshold for companies competing for specialized expertise.
The Bottom Line
ProvenBase isn’t the first company to claim it can find hidden talent. It is, however, the first to produce a credible architecture—and credible endorsements—that suggests it may actually have cracked the code.
With Fortune 100 adoption accelerating, a sophisticated multi-source discovery engine, and one of the most respected sourcing minds in the world joining its advisory board, the company has earned the industry’s attention.
And for organizations locked in a global fight for scientific, technical, and hard-to-find talent, deep discovery is no longer optional. It’s competitive survival.
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