Greenhouse can't answer it solo.
ATS in Greenhouse is only one input; the hiring decision stalls without score fit alongside it.
Build a Candidate Matching Agent withGreenhouse and Ashby
Right now the hiring decision means stitching Ashby + Greenhouse by hand. Poor job-candidate fit causes 50% of early turnover, so the work lands late and half-blind.
Match candidates to roles needs 2 systems to agree.
Today they don't, so the hiring decision guesses.
Today they don't, so the hiring decision guesses.
Ashby tells a different story.
What Ashby knows about score fit rarely flows back to Greenhouse. Two tools, one unreconciled gap.
Ashby catches it quietly.
Recommend alternatives surfaces in Ashby ahead of time, but that tab is closed during candidate matching.
Under The Hood
Match candidates to roles from Greenhouse and Ashby in one prompt, nothing to stitch. Already connected.
01
Read match candidates to roles from Greenhouse (applicant tracker)
ATS
02
Query score fit from Ashby (applicant tracker)
Job Description Databases
03
output
Agent-ready output
The brief for the hiring decision: Match candidates to roles, score fit, recommend alternatives, predict success, riskiest items surfaced and owned.
The Context Store
ATS from Ashby + Greenhouse, pre-joined before the agent runs.
Ashby + Greenhouse get reconciled up front for candidate matching: ATS, Job Description Databases, Skills Taxonomies, Performance Data mapped to a single role view instead of 2 separate APIs.
Your agent queries one surface instead of three APIs. Faster responses, lower cost per query, and results that work because the relationships were built before you asked the question.
PRE-JOINED ROLEUNIFIED SCHEMAONE API SURFACE
The Prompt
Copy. Paste.
a Candidate Matching Agent
Two steps. Your data, your results, under 60 seconds.
01install
Connect the Airbyte Agent MCP02copy and run
Help me turn Greenhouse and Ashby into a single hiring decision I can act on.
SETUP
Use the Airbyte Agent MCP. 2+ connected sources behind one natural-language surface.
WORKFLOW
connect Greenhouse and Ashby -> read ATS, Job Description Databases, Skills Taxonomies, Performance Data -> merge into one role view -> rank and explain. Each unconnected source is a one-time browser auth away.
TASK
Match candidates to roles, score fit, recommend alternatives, predict success and surface the brief: highest-risk roles first, each with a recommended next step.The Outcome
The hiring decision that needed 2 hours now finishes while you read this. Now your agent can fix it.
10x
Faster
10x speed: candidate matching turns a 2-hour hiring decision into under a minute.
90%
Cheaper to run
~90% cheaper: Candidate Matching reuses the 2 connectors you already pay for.
2 -> 1
Tools, one query
2 -> 1: candidate matching answers Greenhouse and Ashby in a single query.
Based on internal benchmarks comparing Context Store queries to sequential API calls across equivalent datasets.
01 · Output
Risk-scored output
Candidate Matching ranks each role by risk, not by name. The top of the list is where to start.
02 · Signal
Where the tools disagree
Greenhouse vs Ashby mismatches on match candidates to roles get called out so you decide, not the math.
03 · Context
The why, attached
Score fit from Ashby sits beside each item, letting you match candidates to roles without switching tabs.
04 · Action
Next action per item
Candidate Matching closes each role with a recommendation. The owner and the move. Ready to run.
05 · Brief
Built to match candidates to roles
Hand the brief straight to the hiring decision. Every figure traces back to Greenhouse and Ashby.
More people ops agents like Candidate Matching
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IT onboarding Agent
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Common questions
Didn't find your answer? Please don't hesitate to reach out.
Can Candidate Matching really join Greenhouse and Ashby on one role?
It matches them on a shared role key, so candidate matching reads one record, not 2 API responses.
Does Candidate Matching replace Greenhouse?
No, it reads Greenhouse and writes back the brief. Your record systems stay put.
Can I tweak what Candidate Matching returns?
Edit the TASK line. Change the ranking, the brief format, or which of Greenhouse and Ashby it leans on.
How do I trust the hiring decision?
Candidate Matching cites a source per line. ATS from Greenhouse, the rest from Ashby. So any figure traces back.
Stop tab-switching to match candidates to roles. Let the agent read Ashby + Greenhouse.
Connect Greenhouse and Ashby (plus 47+ more) and ship candidate matching today to match candidates to roles.
