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Create talent profiles on individuals that go beyond a resume.
Most top AI practitioners aren't actively job searching, and their technical contributions exist across fragmented platforms such as coding repositories, academic conferences, model hubs, patent databases, and technical communities.
Talent acquisition teams need objective evidence to justify candidate decisions, especially for highly compensated AI roles where hiring mistakes are costly.
Manually verifying technical credentials across multiple platforms is time-consuming and inefficient, slowing down hiring cycles.

Resume keywords and job titles don't capture true AI expertise. When every AI hire is critical and talent is scarce, you need proof not promises.

Find multimodal AI experts, retrieval system builders, or AI safety researchers, not generic "machine learning engineers."

Identify AI talent with breakthrough contributions before they're widely recognized and heavily recruited.

Present hiring managers with verifiable AI credentials: conference papers, code impact, AI patents, competition wins.

Automatically append AI credentials in your system of record.

Cultivate relationships with AI practitioners working on emerging techniques and specializations relevant to your roadmap.

Identify and engage exceptional AI builders while competitors are still screening generic applications.
ZoomInfo AI Builder Catalog is a data cube that helps recruiters find AI talent based on verifiable proof-of-work signals - including open-source contributions, academic publications, patents, and competition wins - rather than relying solely on resumes or job titles.
Most resumes only tell part of the story. The AI Builder Catalog shows what candidates have actually built - their code, research, patents, and competition wins. Instead of taking self-reported claims at face value, you get verifiable proof of real technical ability, so it’s easier to identify true experts and make confident hiring decisions.
Most top AI practitioners are passive: their meaningful contributions are spread across fragmented platforms like coding repositories, academic conferences, model hubs, patent databases, and technical communities. Manually validating this work is time-consuming and slow.
Proof-of-work signals may include open-source projects with code impact, academic publications, patents, model competition rankings, and other technical achievements that validate real AI expertise. Contact sales for more details.
This is where ZoomInfo AI Builder Data Cube comes to the rescue. Instead of broad searches like “machine learning engineer,” the platform helps identify specialists such as multimodal AI builders, retrieval system experts, or AI safety researchers. Click here and get started.
Instead of manually checking multiple platforms to confirm a candidate’s technical credibility, the ZoomInfo AI Builder Catalog consolidates proof-of-work into a single profile - dramatically reducing vetting time.
The ZoomInfo AI Builder Catalog provides objective, verifiable evidence of a candidate’s technical expertise, helping talent acquisition teams demonstrate the impact and credibility of their hiring decisions. Instead of relying on self-reported resumes, recruiters can show leadership real proof-of-work - such as open-source code contributions, academic publications, patents, and competition wins. These data-driven insights make it easier to justify high-value AI hires, reduce hiring risk, and align HR, recruiting, and business stakeholders around measurable quality indicators.
Yes - the AI Builder Catalog integrates easily with your existing applicant tracking or CRM systems. You can automatically enrich candidate records with verified proof-of-work insights, like open-source contributions, research papers, and patents. That means your team can access complete, validated AI profiles right where you already work, without toggling between tools. By syncing these insights into your system of record, you streamline sourcing, evaluation, and reporting - all while keeping your data clean and centralized.