Gradient provides an AI-powered hiring assessment platform that evaluates candidates through real-work simulations rather than resumes or rehearsed interviews. The platform gives every candidate access to the same AI tools in a timeboxed, private environment, allowing employers to observe authentic workflows and AI fluency. Assessments are completed asynchronously, eliminating scheduling barriers while delivering consistent, unbiased evaluation signals.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional hiring methods like resumes, behavioral questions, and live screen shares fail to assess AI fluency in a post-AI world. Resumes can be AI-written and keyword scans filter for words rather than actual capability, while behavioral interviews elicit polished talking points instead of real evidence. Live screen shares provide high signal but are costly, unscalable, and expose candidate personal data.
Solution
Gradient offers an asynchronous, AI-fluency assessment platform where candidates complete real-work tasks on their own schedule. The platform provides every candidate with the same standardized AI tools, eliminating advantages from paid subscriptions and ensuring fairness. Employers can observe how candidates gather information, make decisions, and evaluate AI-generated outputs through their actual work process. Assessments are timeboxed for consistency while remaining flexible enough for candidates to complete without calendar coordination. The platform also supports skill-building and brand-specific AI configurations, helping teams measure and improve AI fluency across their organization.
Target Audience
Primary customers are hiring managers, talent acquisition teams, and organizational leaders at companies seeking to evaluate and build AI fluency in their workforce.
Features
- Standardized AI tool environment that levels the playing field by giving every candidate identical access to AI capabilities
- Real-work assessments that capture how candidates think, collaborate with AI, and validate outputs rather than evaluating finished products
- Timeboxed, self-scheduled assessments that eliminate coordination overhead and scale without draining team resources
- Privacy-focused design that allows candidates to edit AI memory and add skills without exposing personal data
- Reusable AI "skills" framework that packages brand guidelines, templates, and instructions for consistent, on-brand AI-generated work
- Progressive disclosure architecture in skills that optimizes token usage and keeps AI focused on the most relevant instructions