ReadyFirst provides a data-driven cognitive testing platform built specifically for 911 dispatch hiring. Its role-specific battery measures working memory, divided attention, and processing speed to identify candidates most likely to complete training, replacing generic aptitude tests that fail to predict dispatcher success. The platform integrates into existing recruitment funnels between application and interview stages, delivering ranked candidate lists to agencies.
Funding
Funding not disclosed
Founders
Product
Problem
Emergency communications centers rely on hiring tools designed for office work—resumes, references, and generic aptitude tests—that fail to measure the cognitive skills dispatch actually requires, such as working memory under load, divided attention, and rapid decision speed. This mismatch contributes to persistent attrition, with industry data showing only 71% average retention across U.S. emergency communications centers and traditional screening rarely flagging at-risk candidates in advance.
Solution
ReadyFirst provides a role-specific cognitive battery that evaluates candidates on the mental capabilities essential to 911 dispatching, including working memory, attention, and processing speed. The platform uses a four-step protocol that maps integration points with an agency's current hiring process, enrolls candidates through a self-service portal via CSV or manual upload, and delivers a ranked list identifying the candidates most likely to complete training. The test projects a fit rank with a confidence score, offering a clearer signal than legacy screening methods. The solution is designed to drop into existing recruitment funnels without requiring process replacement, positioning between the application stage and panel interview.
Target Audience
The primary customers are 911 emergency communications centers and public safety agencies seeking to improve dispatcher hiring accuracy and reduce training attrition.
Features
- Role-specific cognitive battery measuring working memory, divided attention, and processing speed
- Candidate fit ranking with projected success probability versus legacy method rankings
- Self-service portal supporting candidate enrollment via CSV upload or manual entry
- Data-driven comparisons showing divergence from traditional screening outcomes
- Structured 4-step implementation protocol designed for integration without rip-and-replace