The problem
Boolean keyword parsers miss great candidates with non-standard backgrounds. Static matching fails to understand the why behind experience or predict how candidates will actually perform on technical challenges.
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AI-driven problem solving analysis. Contextual resume mapping that identifies logic over legacy formatting.
Boolean keyword parsers miss great candidates with non-standard backgrounds. Static matching fails to understand the why behind experience or predict how candidates will actually perform on technical challenges.
Neural Match v4.2 moves beyond keyword matching to understand the cognitive patterns behind a candidates history. It maps experience against technical architecture logic nodes, predicting problem-solving speed and approach.
Neural Match integrates with your ATS workflow, analyzing every candidate against role requirements. Matches include detailed reasoning explaining why each candidate fits, enabling confident decisions without manual resume review.








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Neural Match understands the semantic meaning and cognitive patterns behind experience, not just keyword presence. It predicts how candidates think and solve problems.
Cross-role intelligence specifically identifies candidates whose skills transfer across domains, surfacing talent that keyword matching would miss entirely.