Findem

LinkedIn search is good at finding people with specific job titles at specific companies. It is less good at finding people who consistently earn promotions stay at companies longer than average show patterns of cross-functional collaboration or have built specific capabilities through projects rather than titles. Findem uses attribute-based search to surface those patterns. You define what you are looking for in terms of characteristics and behaviours not just credentials and the AI searches across a dataset of professional signals including funding events open source contributions publication authorship job change frequency and other data points that LinkedIn does not surface through boolean search. The talent pipeline builder populates lists of candidates matching specific attribute profiles for proactive relationship building before roles open. The diversity sourcing capability identifies underrepresented talent based on attribute matching rather than just pipeline representation percentages. Findem integrates with major ATS and CRM platforms and pricing is enterprise custom. One honest observation: attribute-based sourcing is powerful when the attributes are well-defined and the signals Findem tracks are relevant to what you actually value in a hire. For roles where the performance predictors are genuinely about track record and behaviour rather than credential the signal quality is high. For roles where credentials matter more the advantage narrows. For talent acquisition teams doing sophisticated sourcing for competitive technical commercial and executive roles where resume-based search consistently misses the strongest candidates Findem offers a meaningfully different way to find people.

• Category: Human Resources
• Pricing: Paid
• Rating: 4.4 / 5 (0 reviews)
• Platforms: Web

Key features

• Attribute-based search — Find candidates based on behavioural patterns career signals and characteristics rather than job titles and keywords
• 3D data signals — Searches across funding events open source contributions publication history job change frequency and other non-resume signals
• Talent pipeline builder — Populates proactive candidate lists matching specific attribute profiles for relationship building before roles open
• Diversity sourcing — Identifies underrepresented talent through attribute matching rather than filtering on demographic proxies
• ATS and CRM integration — Connects with major enterprise ATS and talent CRM platforms for workflow integration
• Candidate engagement — Outreach and engagement tools for connecting with sourced candidates
• Market intelligence — Talent market data on candidate availability and competitive hiring landscapes
• Custom attribute definition — Define role-specific attribute profiles tailored to what actually predicts success in each position

Pros & Cons

Pros

• Attribute-based search that goes beyond credentials and titles surfaces candidates that keyword and boolean search consistently misses
• 3D data signals across funding events open source and other sources capture professional behaviour beyond what a resume contains
• Diversity sourcing through attribute matching rather than demographic proxy filters is more sophisticated than most diversity sourcing approaches
• Talent market intelligence for understanding candidate availability and competitive landscapes
• Proactive pipeline builder for building candidate relationships before specific roles open

Cons

• Attribute-based advantage is highest when performance predictors are genuinely behavioural — less differentiated for credential-heavy roles where titles and degrees are the primary qualifier
• Enterprise custom pricing with no public rate card requires a full sales conversation before evaluation
• Signal quality depends on data availability — candidates with limited public digital presence across the platforms Findem tracks produce weaker attribute profiles
• Implementation and attribute definition to set up role-specific profiles requires initial investment before the sourcing produces reliable results

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