Nolais
Nolais provides a continuous measurement platform that assesses how effectively employees work with AI using real-work simulations rather than quizzes or self-reported data. The platform scores individuals across five dimensions—AI Judgment, Supervision, Verification, Tool Fluency, and Execution—and enables organizations to measure, improve, and re-measure to prove the impact of training investments.
- Data & Analytics
- Artificial Intelligence
- Enterprise Software
- HR Technology
- Software Only
- AI Agents
- Developer Tools
Funding
Founders
Founder details are not available yet.
Product
Problem
Organizations are rapidly adopting AI tools but have no reliable way to measure whether employees actually use them effectively. Training budgets are spent without any signal of impact, and there is no baseline to understand who on the team uses AI well or what changed as a result of improvement efforts.
Solution
Nolais provides a continuous measurement platform that assesses how effectively people work with AI using real-work simulations rather than quizzes or self-reported data. Each team member receives an AI effectiveness score across key dimensions including AI judgment, supervision, verification, tool fluency, and execution. The platform enables organizations to measure, improve, and measure again through a repeatable three-step cycle, producing concrete evidence of what changed after training or workflow adjustments.
Target Audience
Primary customers are organizations and team leaders who have adopted AI tools and need to understand, improve, and prove workforce AI effectiveness, including roles such as product marketing managers and other knowledge workers.
Features
- Real-work AI effectiveness scoring through simulations with actual tools and decisions, not self-reported assessments
- Individual performance scores across five dimensions: AI Judgment, Supervision, Verification, Tool Fluency, and Execution
- Identification of knowledge gaps with specific unknown areas flagged for each user
- Baseline establishment to reveal who on the team actually uses AI well
- Repeatable assessment cycle to demonstrate measurable improvement over time
- Candidate assessment capability for hiring decisions using the same real-work AI simulations