Advancing the frontiers of AI and recruitment technology.

Recruiting teams are drowning in admin work while great candidates slip through the cracks. AI recruiting assistants are transforming how companies hire by automating screening, sourcing, interviewing, and candidate engagement—freeing up recruiters to focus on what matters: building relationships. Here's everything you need to know about AI hiring assistants and how to implement them effectively.

Job boards are broken. Recruiters ghost you. Applications vanish into the void. But a new generation of AI recruiting tools is changing everything—helping candidates find better roles faster, with less stress. Here's how to use AI to land your next job.

Human oversight has long been positioned as the critical safeguard against AI discrimination in hiring. New research from the University of Washington reveals a troubling reality: when humans collaborate with biased AI systems, they overwhelmingly adopt—rather than counteract—the machine's prejudices. We examine the implications for AI-assisted recruitment and what organizations must do differently.

Large Language Models can replicate and amplify societal biases, particularly in high-stakes domains like hiring. We detail our comprehensive approach to detecting, preventing, and monitoring bias in recruitment AI—from pre-training data curation to continuous evaluation metrics—and introduce our specialized bias benchmark for hiring systems.

Job seekers are using sophisticated prompt injection techniques to manipulate AI screening systems by embedding hidden instructions in resumes. We developed advanced detection algorithms that identify and neutralize these attacks with 100% precision, ensuring fair and authentic candidate assessment.