Give every applicant
a fair first read.
Slate reads every application against the role, runs a structured, job-relevant screen, and gives each candidate a clear, evidence-based summary with the reasons. So a small team reviews everyone fairly, not just the first ten.
One role free
No card required
Every read has its reasons
240 applications read against the role
fair rubric
Renata Alvarez
Strong fit40 SaaS accounts, churn 14% to 8%
Marcus Bell
PromisingSupport lead owning renewals
Priya Menon
Strong fitExpansion 118% net revenue retention
Aisha Nasser
PromisingCareer changer, strong comms
Jordan Wu
PromisingOnboarding specialist, technical
Tom Callahan
LimitedNew-logo sales, little retention
18 shortlisted, with the reasons
a human decides
Most applications are never really read.
It is not a lack of care. A small team cannot give two hundred applications the same close attention, so the pile gets skimmed from the top. Strong people further down never get a fair look, and the read that shapes a career comes down to when someone applied and how a resume was formatted.
The answer is not to skip the first round. It is to give every applicant the same structured read, with the reasons written down.
240 applications, one role
today
200+
applications for a single open role at a growing company
6s
the average first pass over a resume before it is set aside
the first 10
get a real read. The rest get skimmed, or never opened
A fair read is a structured read.
Three steps, run the same way for every applicant, from the first to the two hundredth.
Read every application against the role
Slate reads each application in full, not just the top of the resume, and reads it against the role you defined. The same role, the same attention, for the first applicant and the two-hundredth.
Role
Customer Success Manager
Seed-stage SaaS · fully remote (US)
readingManaged a book of 40 mid-market SaaS accounts worth $2.1M in ARR. Cut gross churn from 14% to 8% over three quarters.
Run a structured, job-relevant screen
It works through the role's must-haves one by one and checks each against the evidence in the application. Job-relevant only. Name, school, and background are not part of the screen.
Structured screen
Get an evidence-based summary
For every candidate you get a fair summary: the fit, the reasons in plain words, and the exact lines they came from. You review the reasons and make the call.
Renata Alvarez
Strong fitRenata 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.”
A fair, evidence-based read of every candidate.
Real applications for one role. Pick a candidate, then move between the summary, the evidence behind it, and the fit against the must-haves. Every reason is tied to a line from the application.
Renata Alvarez
Strong fitFour years owning SaaS accounts, with a specific, evidenced churn result.
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.
Strengths
- Owned a real SaaS book
- A measured churn reduction
- Writes clearly and concretely
Gaps to verify
- Accounts were mid-market; this role skews smaller and earlier
Slate surfaces the evidence. A human makes the hiring decision.
Run this on your own roleA screening copilot, not a reject engine.
Reads every applicant against the role
Not keyword matching and not the top ten. Slate reads each application in full and reads it against the role you defined, giving the last applicant the same attention as the first.
Structured, job-relevant screening
It works through the role's must-haves one at a time and checks each against the evidence, so the read is consistent from one candidate to the next.
Evidence-based summaries
Every judgment is tied to a verbatim line from the application. You see the reason and the exact words it came from.
Bias-reduction by design
Name, age, gender, school and employer prestige are kept out of the screen. Slate judges the work and the evidence, not the person.
A human always decides
Slate never auto-rejects. It produces a fair first read and leaves the call, and the accountability, with your team.
Model-agnostic
Slate routes across 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.
The model is the engine, not a bolt-on.
Screening unstructured applications at scale, and explaining the read with reasons, is not something rules or keyword filters can do. It became possible with modern language models. That is why Slate is built around the model from the first line, and why it is model-agnostic: it routes across models per task and is never tied to one provider.
Applications are messy
Resumes, notes and cover letters in every format. No two are laid out the same way.
Language models do the reading
Reading prose against a role and saying, with reasons, how it lines up is exactly what modern language models are for.
A sourced, structured read
Out comes a fair summary, the fit, and reasons tied to the exact lines. Consistent enough to compare across a whole pool.
Fair by design. A human decides.
Models can carry bias from the data they were trained on. We do not pretend otherwise. We reduce it by constraining the screen to job-relevant evidence, applying the same rubric to everyone, and making every reason auditable, then leaving the decision to a person.
What Slate does
- Screens only on evidence relevant to the role
- Keeps name, age, gender, school and employer prestige out of the read
- Applies one consistent rubric to every applicant
- Ties every reason to a verbatim line you can check
- Says plainly when the evidence is thin or unclear
What Slate does not do
- Never auto-rejects a candidate
- Never makes the hiring decision for you
- Does not score personality or predict a person
- Does not run a background check or read protected data
- Does not claim to be infallible
Fairness is not a setting we toggle on. It is how the read is built, and we would rather be honest about the limits than oversell the certainty.
Read our fairness approachRead by the people who do the hiring.
We had 300 applicants for one role and were reading maybe forty of them. Slate gave every one the same structured read, with the reasons attached, so we could shortlist from the whole pool in an afternoon instead of the top of the inbox.
Jordan Ellery
Head of Talent, Fathom Robotics
What sold me is that it does not decide. It shows the evidence and the gaps, and we still make the call. The candidates we advanced were ones I would have missed, and I could see exactly why they were surfaced.
Maria Santos
Founder and CEO, Cadence Health
Illustrative feedback from early-access teams
Start free, pay when it earns its place
Screen one open role free. Move to Team when you want every applicant read across every role, with summaries your whole team shares. Prices show in your local currency.
Free
Screen your first open role
Read one open role against a small batch of applicants and get a fair, evidence-based summary for each, with the reasons. No card required.
Start free- 1 open role
- Up to 50 applicants a month
- Evidence-based summary per candidate
- The reasons, each tied to a quote
- 1 seat
For a founder doing their own first-round reads.
Team
Read every applicant, not the first ten
Screen every open role at real volume, with evidence-based summaries your whole hiring team shares, comments on, and exports to your ATS.
Start free trial- Up to 10 open roles
- Up to 1,500 applicants a month
- Evidence-based summaries with reasons
- Shared workspace and reviewer notes
- Custom rubrics per role
- Export to ATS, CSV and PDF
- Up to 8 seats
For hiring teams who want every applicant read the same way.
Scale
Hiring across many roles at once
Screen at high volume across your whole org, with SSO, an audit log of every read, custom rubrics, data residency and a named partner.
Contact sales- Unlimited roles and applicants
- SSO, SAML and SCIM
- Audit log of every screen and reason
- Custom rubrics and scoring review
- Data residency and retention controls
- API access and ATS integrations
- Unlimited seats and a named partner
For talent teams running many roles where fairness has to be provable.
Prices are shown in your local currency, converted from the USD home price at a fixed rate. Sales tax is added where it applies. Annual plans are billed once a year at the lower per-month rate. Slate surfaces evidence and reasons on every plan. A human always makes the hiring decision.
Before you start
Give every applicant a fair first read.
Start with one open role, free. Paste the role and a few applications and see the evidence-based read for yourself. No card required.