SeeTalent.ai provides conversational AI-powered assessment experiences tailored to specific job roles, simulating realistic scenarios through multi-agent interactions. The platform supports leadership selection and volume recruitment with an independent scoring layer and fairness testing to reduce adverse impact. Its agentic AI creates personalized, dynamic conversations that capture how candidates think, communicate, and adapt under pressure.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional recruitment assessments often rely on standardized, one-size-fits-all formats that fail to capture real-world job complexity and can introduce bias into hiring decisions. This leads to poor person-role fit, reduced diversity, and missed opportunities to identify top talent who may not perform well in conventional testing environments.
Solution
SeeTalent.ai delivers unique assessment experiences tailored to specific job roles using agentic, conversational AI that simulates realistic scenarios reflecting real-world complexity. The platform employs multi-agent AI systems where candidates interact with multiple AI agents in layered, dynamic conversations, enhancing realism and challenge. Each assessment journey is personalized at scale, ensuring high engagement and tailored outcomes. An independent scoring layer captures signals from these interactions, while iterative validation and fairness testing manage trade-offs between validity and impact to maximize both utility and fairness.
Target Audience
Primary customers are organizations seeking fair, talent-focused recruitment processes, including HR teams managing leadership selection, volume recruitment, and role-specific hiring across various business sectors.
Features
- Multi-agent conversational AI that simulates realistic, role-specific scenarios with distinct agent personalities and roles
- Personalized assessment journeys that adapt to each test-taker for high engagement and tailored outcomes
- Independent scoring layer that captures behavioral signals from candidate interactions
- Fairness and adverse-impact testing that identifies subgroup differences and manages trade-offs between validity and impact
- Configurable, sector-specific scenarios with objectives and constraints for leadership selection
- AI-augmented reporting that provides insights into candidate thinking, communication, and adaptability under pressure