Fifty read, one hundred and fifty skimmed
Time ran out before the pile did.
Greenhouse AI candidate matching and ranking for teams that want a shortlist they can explain
Greenhouse AI candidate matching and ranking automation that scores applicants against your rubric, shows the evidence behind each position and honors every AI opt-out
Greenhouse records, per candidate and per job, whether a candidate has confirmed that they do not want AI-assisted review, and confirming an opt-out deletes the match scores already computed for that job. BoldBellows records the application, the job and the scoring rubric version before any candidate is compared, reads each candidate's AI opt-out status for the job and leaves anyone who opted out unscored, then passes a model only the fields your rubric names, asks it to score each criterion with a quote from the application as evidence, sums the result into a ranked list with the reasons beside every score, writes the ranking to the application as a note for the recruiter, and moves no one between stages and rejects no one. Demographic answers and EEOC data are never read.
View Pricing
From $1,130, paid once. Rank Greenhouse applicants with AI.
The checks behind every Greenhouse AI proposal
- Rubric you wrote six criteria, versioned
- Evidence quoted every score explained
- Opt-outs honored never scored
- People decide no automatic moves
- Reviewable mapping The field map is documented and signed off before launch
- No meter running $1,130 covers design, build, tests and handover; nothing accrues afterwards
01 · the black-box shortlist problem
A ranked list with no reasons is a decision nobody can defend
Two hundred applicants for one opening means a recruiter reads fifty and skims the rest, and which fifty depends on the day. A keyword filter rewards the right buzzwords and misses the candidate who describes the same work in other words. A scoring model that only returns a number cannot say why one applicant sits above another, cannot be audited and, in a market with rules on automated employment decision tools, can become a liability. Some candidates have also chosen not to be scored by AI at all.
The right words, the wrong person
Keywords rewarded vocabulary.
A score nobody can explain
No evidence was kept.
- A second delivery makes a second proposal
- A recruiter skims most of the pile
- Scores come with no reasons and no audit trail
- The AI workflow recognises its own work through one key built from the application, the job, the rubric version and the model run
- Every applicant is scored against the same written rubric
- Each score carries a quoted reason and a named reviewer
02 · how it works
How a pile of applicants becomes a ranked list with reasons attached
An event becomes a proposal in three stages, each with its own evidence.
- 01
Judge before acting
Before anything is prepared for the AI workflow, the Greenhouse event is checked against the agreed admission rule.
- 02
Check, score, explain
Opt-out status is read, the model scores each rubric criterion from the application, and every score is stored with a quoted passage.
- 03
Rank, note, review
The scores are summed into a ranking, the ranking is written to the application as a note, and a recruiter decides who moves.
Facts about Greenhouse and AI that shaped the build
Opted out means no score
Greenhouse records, per candidate and per job, whether a candidate has confirmed that they do not want AI-assisted review, and confirming an opt-out deletes the match scores already computed for that job, so the route reads that status before it ranks anyone and never rebuilds a score for someone who opted out.
Opted out means no score
Confirming an AI opt-out in Greenhouse deletes the match scores already computed for that job except where a recruiter has overridden them, so the route reads the status first and never rebuilds a score for someone who opted out.
Replay safety
Because one key built from the application, the job, the rubric version and the model run is stored with each record, replaying an event leaves the AI workflow unchanged if the work exists.
03 · what ships in the build
Inside the ranking route: the parts that do the scoring
The route grows in three steps: Basic, then Branch, then Guardian.
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Event triage
Looks at each Greenhouse event and chooses between act, wait and discard, with notes.
BasicStable identity ledger
Holds a source key and a model-run key on each proposal, so a repeat finds the decision it already made, in the Greenhouse AI Candidate Matching and Ranking service.
BasicApproved-fields list
Keeps one reviewed list of fields that may reach the AI workflow and refuses additions without sign-off.
BasicRubric scorer
Scores each criterion from the application and quotes the evidence.
BranchApplication-and-rubric matcher
Finds the existing proposal through one key built from the application, the job, the rubric version and the model run, or proves there is none.
BranchOpt-out and exclusion matrix
Decides who is scored, who is skipped and which fields the model may see.
BranchRanking register
Tracks mismatches between Greenhouse and the AI workflow until someone closes them.
GuardianAdverse-impact monitor
Compares outcomes across groups using the four-fifths comparison and flags a gap for review.
GuardianOperations board
Gives the team one place to see blocked work between Greenhouse and the AI workflow.
Guardian04 · who it's for
Aimed at professional services firms that want to rank the applicants for an opening against a written rubric, show a recruiter the evidence behind every position, and leave the decision to a person
Recruiters want a place to start. Candidates want to be read fairly, and the company needs to be able to show how a shortlist was made.
Recruiter
"Where do I start with 200 applicants?"
A ranked list with the reasons beside every position.
Hiring manager
"Why is she above him?"
Each score shows the passage it came from.
Head of talent
"Keep us fair."
Outcomes are compared across groups on a schedule.
Compliance lead
"Automated tools need a paper trail."
Rubric, model and reviewer are stored for every score.
Candidate relations
"Respect candidates' choices."
Anyone who opted out of AI review is left unscored.
Managing director
"I want speed without risk."
The route advises and a person decides.
The quote reflects applicants, scores and reviews
Cost your ranking route, one rubric choice at a time
Basic starts at $1,130.
View Pricing
- One setup fee
- Range shown first
- PDF handover included
05 · compare your options
What a keyword filter on a resume pile, a zap and a rubric-based ranking route each do for the AI workflow
Each can sort a pile. Only one scores against a written rubric, quotes its evidence and respects opt-outs.
| How a run starts | A keyword filter | A generic AI scoring tool | Our rubric-based ranking route |
|---|---|---|---|
| What starts the work | An admin on a busy day | Anything the trigger matches | Only changes on your in-scope list |
| How identity is decided | Checked against old notes | A lookup that may return several | One key: application, job, rubric version and model run |
| What reaches the AI workflow | A handwritten note turned digital | The default field set | A ranked list with quoted evidence, advising a named reviewer |
| After an uncertain result | An email thread to sort it out | Fails quietly | Uses one key built from the application, the job, the rubric version and the model run to settle what already exists |
A slow event catches up
A late Greenhouse notice is compared with the stored checkpoint; anything older than the current proposal is closed with a note.
A candidate confirms an AI opt-out after being scored
The next read shows the opt-out, the stored score is withdrawn from the recruiter's view, nothing new is computed, and the application goes to manual review. It searches the AI workflow on one key built from the application, the job, the rubric version and the model run, weighs what it finds against the plan and logs the verdict. Only when nothing is found does the route make a new proposal.
One key built from the application, the job, the rubric version and the model run links each Greenhouse record to its the AI workflow proposal for the life of the route.
Pricing
Build your Greenhouse AI Candidate Matching and Ranking price
Pick a package, answer three short questions about how Greenhouse data should reach AI Candidate Matching and Ranking, and your price and turnaround move as you choose.
06 · process & getting started
Six steps to a shortlist you can explain
Six steps, named outputs, and a review after go-live.
- Step 01
Write the rubric
We turn the role into six or fewer criteria, each with a plain definition of strong, adequate and weak evidence.
- Step 02
Approve access
We take scoped access to Greenhouse, agree where the model runs and fix the identifiers every proposal will carry.
- Step 03
Agree the guardrails
Which fields the model sees, who reviews, how opt-outs are handled and how outcomes are monitored are agreed in writing before a model is switched on.
- Step 04
Try the awkward records
Unusual, incomplete and repeated records are run through a test the AI workflow so the route's answers are known.
- Step 05
Launch with notes
The last step is release: a defined start, a review window and a PDF you can keep.
- Step 06
First-month watch
The opening weeks are monitored for retries, delays and mismatches, and the results are summarised for you.
07 · turnaround
How long the AI Candidate Matching and Ranking packages take
The days count from the moment access to Greenhouse and the model is approved.
Basic
6 to 10 business days
Branch
10 to 16 business days
Guardian
16 to 24 business days
08 · before we start
What we ask of you
Authorisation to reach the Greenhouse objects in scope
A Greenhouse Harvest v3 credential created by a Site Admin, your written criteria for the role and a named reviewer for each opening
The Greenhouse events and object types you want included
Which Greenhouse events are urgent and which can wait
The current owner of each the AI workflow area the route will write to
Notes on any past problems between Greenhouse and the AI workflow
09 · security and ownership
Access you can revoke, data you can name
Only agreed Greenhouse fields reach the model.
Clean separation
Greenhouse keeps doing what it does and the AI workflow keeps doing what it does; the connection between them is the only new thing.
Scoped, revocable access
Permissions are written down, minimal and reversible.
Allowlist, not blocklist
New fields in Greenhouse do not flow into the AI workflow until someone adds them to the map on purpose.
Idempotent by design
The same event processed twice gives the same result in the AI workflow, because one key built from the application, the job, the rubric version and the model run decides create or update.
Minimal logging
Evidence of a run is kept as references, not as copies of data.
Full handover
The PDF names each rule, credential and owner so your admins are never guessing.
10 · verified reviews
What BoldBellows clients say
Verified reviews from business owners who use BoldBellows automations every day, from marketing and sales to support and operations.
AI HR & Recruitment Automation
Our HR team was drowning in applications. BoldBellows automated screening, skills-based filtering and interview scheduling.
It saves us hours every week and means we only interview qualified people. Hiring is now faster, better organized and more professional.
AI Workflow Automation for Agencies
Running a digital agency with many clients was overwhelming. BoldBellows built one automation dashboard that tracks tasks, sends updates and creates client reports automatically.
Clients love the transparency and we love the time we get back. Productivity is up, and project delays have dropped to almost zero.
AI Booking & Scheduling Automation
Our coaching business needed a better way to schedule. BoldBellows automated all of it: bookings, reminders, cancellations and follow-ups.
No-shows fell by 60% and clients enjoy how smooth it is. It feels personal, not robotic. One of the best upgrades we’ve made.
AI Translation & Localisation
When we expanded abroad we needed fast, accurate translations. BoldBellows built an AI translation system that turns our content into several languages instantly.
The translations read naturally and suit each culture. We now serve customers in five new countries without hiring translators. BoldBellows helped us go global.
AI Accounting & Invoice Automation
BoldBellows automated our whole invoicing process: creating invoices, sending reminders and tracking payments.
Late payments dropped sharply, and our accounting team finally has time for strategy instead of repetitive admin. Worth every penny.
AI Data Entry & Reporting Automation
We used to spend hours collecting data and building weekly reports by hand. BoldBellows automated all of it.
The reports are clean, visual and easy to read, and our managers rely on them for quick decisions. Human error is gone and our numbers are more accurate across the board.
AI E-commerce Listings Automation
BoldBellows automated our product listings. The AI writes descriptions, organizes photos and publishes listings across several marketplaces.
It even answers customer questions instantly. Our store looks more professional and sales have noticeably increased.
AI Customer Journey Automation
We wanted a smoother path from first contact to purchase. BoldBellows built an AI system that guides each customer there automatically.
It sends personalized messages, recommends products and follows up at just the right moment. Customer retention has improved dramatically.
AI Document & Contract Automation
Onboarding was slow because we wrote every contract by hand. BoldBellows automated the lot: contracts, welcome emails and client setup.
What took 48 hours now takes under 10 minutes, and clients regularly tell us how professional it feels.
AI Chatbot & Customer Support
BoldBellows built an AI support chatbot for our online boutique, and it has changed how we run the business. We used to have two full-time staff answering the same questions all day. Now the AI handles order tracking, product recommendations and even refund requests on its own.
What surprised me most is how natural it sounds. Customers compliment the ‘agent’ without realizing it’s AI. Our support workload dropped by 75% and customer satisfaction went up dramatically.
AI Content & Social Media Automation
Our marketing agency couldn’t keep up with content. BoldBellows set up an AI content engine that writes blog posts and captions and even designs our social media creatives.
It spots trends and suggests topics for us, so we stay ahead of competitors. We now produce three times the content with the same team, and engagement has soared. They didn’t just automate our workflow, they lifted our whole brand.
AI Lead Qualification & Sales Automation
Our sales team wasted hours chasing cold leads. BoldBellows built an AI lead-scoring system that reads behavior, email engagement and buying signals.
It filters out weak leads and sends personalized follow-ups automatically, so our team only talks to people who are ready to buy. Conversions rose 40% in the first month. It paid for itself straight away.
AI Video & Voice Automation
We publish product videos every week, and BoldBellows introduced us to AI video automation. The system writes the script, voices it and produces the finished video in minutes.
The quality is remarkable: professional voiceovers, clean visuals and smooth editing. Production time went from three days to under 30 minutes, and we scaled our video marketing without adding cost.
AI Email & Smart Inbox Management
Our inbox used to be chaos. BoldBellows built an AI email system that sorts messages, drafts replies and flags anything urgent.
It learns how we write and gets better every week. We reply faster and no longer miss important messages. It feels like having a personal assistant working around the clock.
AI Social Comment & DM Automation
We get thousands of comments and messages every week. BoldBellows built an AI system that replies instantly, filters spam and surfaces the important ones.
Engagement is up and our page looks active around the clock. It’s like having a full social media team that never stops.
AI CRM Automation
Our CRM was barely used because updating it by hand was tedious. BoldBellows automated data entry, tagging, segmentation and follow-ups.
Now the CRM is always up to date and our campaigns are far more accurate. It improved our whole sales pipeline.
AI Voice Assistant
BoldBellows built a custom AI voice assistant for our customer hotline. It answers questions, books appointments and handles simple requests.
Customers love how fast it is, and our call-centre workload dropped dramatically. One of the smartest upgrades we’ve made.
AI Automation Partner
BoldBellows is hands-down the best AI automation partner we’ve worked with. Their systems are fast, reliable and built around how our business actually works.
Every automation they’ve delivered, from customer service to content, runs flawlessly. We’ve saved time, cut costs and grown faster than we expected.
11 · questions
AI ranking in Greenhouse: what talent teams ask before trusting it
We collected the questions that decide most purchases and answered them.
Would a basic Greenhouse AI connector be enough?
A shortlist a recruiter can defend is something a zap does well. It does not score against criteria you wrote, respect a candidate's opt-out from AI review or show why one applicant sits above another. If those matter to you, the build is the right fit; if not, we will say a zap is enough.
Does it reject anyone?
No. It writes a ranking and the evidence as a note. People move candidates between stages.
What about candidates who opted out of AI review?
Greenhouse's AI opt-out status is read for each job, and anyone who opted out is left unscored.
What does the model see?
Only the fields your rubric names, and never the demographic resources.
How do you check for bias?
Outcomes are compared across groups with the four-fifths comparison on a schedule, and a gap is flagged for review.
Do we need a bias audit?
Some jurisdictions, such as New York City, require one for automated employment decision tools. We build the records an auditor asks for, and your counsel decides what applies to you.
Can we change the rubric later?
Yes. Each ranking stores the rubric version, so old scores stay explainable.
How do we control what the model can read on the Greenhouse AI Candidate Matching and Ranking service?
Yes. We agree, field by field, what the model sees from Greenhouse and what a proposal may change, and you sign it off first.
Is a custom Greenhouse AI workflow possible?
Yes. You choose which Greenhouse changes qualify, which proposals need approval and who reviews them. Pricing starts at $1,130.
What if the model starts behaving differently in the Greenhouse AI Candidate Matching and Ranking service?
The handover lists every interface the route uses. If one changes, the affected item stops and is flagged instead of being written from a guess. Repairs after your review window are quoted separately. If you searched for custom greenhouse ai candidate matching and ranking automation, this is the service that delivers it.
Give your recruiters a shortlist they can defend
Give your talent team a ranking with the reasons attached
We build the governed Greenhouse AI route around it, starting at $1,130.
Unusual volumes or extra systems are quoted on request.