Product
A fair first read of every applicant.
Slate reads every application against the role, runs a structured, job-relevant screen, and returns a clear, evidence-based summary for each candidate, with the reasons. It surfaces the evidence. Your team makes the call.
One role, read the same way for everyone
Define the role once, and every applicant gets the same structured attention, from the first to the two hundredth.
Define the role once
Give Slate the role: a title, the must-haves, and the nice-to-haves. This is the standard every application is read against, the same for the first applicant and the last.
role: Customer Success Manager · 4 must-haves
Slate reads every application
Each application is read in full and against the role. Slate works through the must-haves, checks each against the evidence, and keeps personal characteristics out of the read. This is the part only modern language models can do.
240 applications · read against the role · one rubric
You get a fair read, with reasons
For every candidate: the fit, a plain-language summary, the reasons tied to the exact lines, and the requirement-by-requirement view. You review and decide.
18 shortlisted · every reason sourced · a human decides
A summary, the evidence, and the fit
Every candidate comes back with a plain-language read, the reasons tied to the exact lines, and a requirement-by-requirement view against the role.
A fair, plain-language read
Two or three sentences on how the application lines up with the role, with the strengths and the honest gaps to verify.
Every reason, tied to a line
Each judgment cites a verbatim quote from the application, so a reviewer can check the read in one click.
Against the must-haves
Each requirement is marked evidenced, partial, or unclear, with a role-match indicator used only to order the read.
Renata has run a book of SaaS accounts for four years and points to a concrete retention result, not just responsibilities. The application shows comfort with a technical product and clear, structured writing. The main thing to check is the size and stage of the accounts she owned.
Directly owned SaaS accounts, which the role asks for
“Managed a book of 40 mid-market SaaS accounts worth $2.1M in ARR.”
Evidences a churn result, not just the responsibility
“Cut gross churn from 14% to 8% over three quarters by rebuilding onboarding.”
Built for a whole hiring pipeline
Reads against the role
Every application is read against the must-haves you defined, in full, not skimmed from the top.
Requirement-by-requirement fit
Each must-have is marked evidenced, partial, or unclear, based only on what the application shows.
Evidence-based reasons
Every judgment is tied to a verbatim line, so a reviewer can check the read in one click.
Bias-reduction by design
Name, age, gender, school and employer prestige are kept out of the screen.
Shared workspace
Reads, notes and shortlists in one place for the whole hiring team, with an audit trail.
Export anywhere
Send the summary and reasons to your ATS, to CSV, or to a PDF. The reasons travel with the candidate.
Fair by design, and a human decides
Bias-reduction by design
Name, age, gender, school and employer prestige are kept out of the screen. Slate judges the work and the evidence, applies one rubric to everyone, and never auto-rejects.
Read our fairness approachModel-agnostic
Slate routes across leading language models per task, so it can trade quality against cost and is never locked to one provider. The read stays consistent as the models improve.
How the AI worksGive every applicant a fair first read.
Start free with one open role, or talk to us about reading every applicant across your whole team.