New applicants pile up, and strong past candidates sit forgotten in the database. Comparing them by hand is slow, inconsistent between recruiters, and prone to error, so good people get missed. A growing share of applications now come from AI agents rather than people, making it even harder to know what's real.
In plain language, or point Dash at the job description.
Dash builds a detailed, editable assessment plan. Adjust criteria, add your own scoring frameworks, keep criteria private that you don't publish in the ad.
Dash scores and ranks every candidate against the plan, new applicants and existing database alike, whether the pool is 25 or 250,000.
Each result carries a written rationale, cited to the CV, screening notes and ATS records, so you can defend any shortlist to a hiring manager.
Assessments evaluate skills and experience only; names are ignored in scoring, so results can't shift with the gender or ethnicity a name implies.
AI agents are mass-applying to roles, and keyword screening can't tell the difference. Dash's structured assessment digs past the padding to what a candidate has actually done.
Dash flags CV gaps worth probing and generates screening and interview questions from the role.
Query Dash, run assessments and surface candidates directly from Slack.