ATS Hiring Intent - Buying Signals (Greenhouse + 4 ATSes)

What does ATS Hiring Intent do?

ATS Hiring Intent aggregates open job postings across five major applicant tracking systems — Greenhouse, Lever, Ashby, SmartRecruiters, and Workday — into one normalized feed and turns the raw job data into per-company buying signals ready for a sales / RevOps pipeline.

Give it a list of company domains. It auto-detects each company's ATS, pulls every open role, normalizes function and seniority across platforms, and (in signals mode) runs each role through Gemini 2.5 Flash to extract intent tags (expanding-sales, evaluating-CRM, series-B-build, platform-build-out, …) and infer the specific vendors / tech stack the company is buying or building on. One composite CompanySignal per refresh tells your reps which prospects just lit up — Stripe is expanding-sales (8/8 AE roles posted, AI-customer focus, vendor hypothesis: OpenAI, Anthropic, NVIDIA).

Zero anti-bot. Zero proxies needed by default. No login. Every data source is an official public ATS endpoint. Replaces $99-$15K/seat tools (Apollo, ZoomInfo, Bombora, Cognism) on the hiring-signal job-to-be-done.

Why use ATS Hiring Intent?

• B2B sales / SDRs — find every prospect actively hiring for a role that signals they're buying your product. Hiring 5 DevOps + 2 Platform Engineers = evaluating IaC + observability tooling. Hiring a VP Sales + 3 AEs = expanding GTM motion. Apollo only counts headcount; this actor explains what they're buying.
• RevOps & GTM intelligence — score your ICP list weekly, build prospect lists from buying-intent tags, replace your stale $1-5K/mo intent-data line item.
• Recruiters & talent intelligence — track hiring velocity at competitors, see which functions/seniorities they're loading up on.
• VC / corporate development — detect Series A → C ramp signals, exec hires, geographic expansion. Headcount-delta tracking with KV-checkpointed monitoring.
• Founders doing competitive intel — type a competitor's domain, see every open role, every detected vendor, every team they're scaling.
• AI / data teams — a clean 30+ field unified ATS schema across 5 platforms with deterministic taxonomy normalization. Drop straight into a vector store or BI tool.

How to use

1. Pick a mode:
   • discover — given domains, detect which ATS each one uses (cheap onboarding pass).
   • jobs — fetch normalized jobs only, no AI.
   • signals — jobs + Gemini intent tags + per-company composite signal (the value tier).
   • monitor — same as signals but only emits deltas vs. the previous run. Best with a daily/weekly schedule.
2. Provide either companyDomains (list of domains — auto-detected) or atsTargets (direct ATS slugs like greenhouse:stripe, lever:palantir, ashby:linear, smartrecruiters:visa, workday:nvidia.wd5/NVIDIAExternalCareerSite).
3. Optionally filter by keywordFilter, functionFilter (engineering / sales / …), seniorityFilter, locationFilter, remoteOnly, postedWithinDays.
4. Run. Results land in the default dataset with a type field discriminator: job, company_signal, ats_discovery, or change_event.
5. Export as JSON, CSV, or Excel from the Apify Console — or pull via API / webhook.
6. Want weekly intent updates? Set mode to monitor and schedule the actor. Subsequent runs only emit new/changed/closed roles + the latest composite signal.

Free trial: the first 10 chargeable events of each run are on the house — enough to validate output shape and signal quality on a single small run before committing budget.

Input examples

1. Discover which ATS your top 5 prospects use.

{
    "mode": "discover",
    "companyDomains": ["stripe.com", "linear.app", "notion.so", "vercel.com", "anthropic.com"]
}

2. Pull every open engineering role at 3 companies, no AI.

{
    "mode": "jobs",
    "companyDomains": ["stripe.com", "anthropic.com", "linear.app"],
    "functionFilter": ["engineering"],
    "seniorityFilter": ["senior", "lead", "principal"],
    "maxJobsPerCompany": 100
}

3. Generate weekly buying signals across a 50-company prospect list.

{
    "mode": "signals",
    "companyDomains": [
        "stripe.com", "notion.so", "linear.app", "vercel.com", "anthropic.com"
    ],
    "maxJobsPerCompany": 50,
    "intentBatchSize": 20,
    "postedWithinDays": 30
}

4. Monitor 200 companies — emit deltas only on the second-and-subsequent run. (Schedule daily.)

{
    "mode": "monitor",
    "companyDomains": ["acme.com", "..."],
    "maxJobsPerCompany": 100,
    "remoteOnly": false
}

5. Skip auto-detection — pass direct ATS targets.

{
    "mode": "signals",
    "atsTargets": [
        "greenhouse:stripe",
        "lever:palantir",
        "ashby:linear",
        "smartrecruiters:visa",
        "workday:nvidia.wd5/NVIDIAExternalCareerSite"
    ]
}

Output

Each row has a type discriminator. Sample enriched job record:

{
    "type": "job",
    "sourceId": "d3bc1ced-3ce4-4086-a050-555055dbb1ff",
    "company": "Linear",
    "domain": "linear.app",
    "atsPlatform": "ashby",
    "atsSlug": "Linear",
    "title": "Senior / Staff Fullstack Engineer",
    "function": "engineering",
    "seniority": "senior",
    "department": "Product",
    "team": "Engineering",
    "location": "Europe",
    "isRemote": true,
    "employmentType": "FullTime",
    "postedDate": "2026-04-21T20:13:45.158+00:00",
    "applyUrl": "https://jobs.ashbyhq.com/linear/d3bc1ced-3ce4-4086-a050-555055dbb1ff/application",
    "intentTags": ["platform-build-out", "going-international"],
    "vendorSignals": ["TypeScript", "React", "GraphQL", "PostgreSQL", "Redis", "Kubernetes"],
    "intentSummary": "This role indicates a focus on expanding the core product platform and international growth.",
    "enrichmentLevel": "enriched"
}

Sample company_signal record:

{
    "type": "company_signal",
    "company": "Stripe",
    "atsPlatform": "greenhouse",
    "atsSlug": "stripe",
    "signal": "expanding-sales",
    "confidence": 1.0,
    "evidence": "8/8 open roles match this signal. Examples: Account Executive AI Sales, Account Executive AI Startups, Account Executive Commercial.",
    "vendorHypothesis": ["Stripe", "OpenAI", "Anthropic", "NVIDIA", "Shopify"],
    "openRolesCount": 8,
    "newRolesLast30d": 8,
    "topFunctions": [{ "function": "sales", "count": 8 }],
    "secondarySignals": [
        { "signal": "series-B-build", "confidence": 0.66, "evidence": "3/8 roles tagged." }
    ]
}

Data fields (selected)

Field	Type	Notes
type	enum	job | company_signal | ats_discovery | change_event
company	string	Display name pulled from board metadata when available
atsPlatform	enum	greenhouse | lever | ashby | smartrecruiters | workday
function	enum	Normalized: engineering, sales, marketing, product, data, design, operations, support, finance, hr, legal, other
seniority	enum	intern | junior | mid | senior | lead | principal | director | vp | cxo | unknown
intentTags	array	22-tag fixed taxonomy — see input schema for the full list
vendorSignals	array	Specific vendor / tech names mentioned in the JD
intentSummary	string	One-line plain-English takeaway from Gemini
salaryMin / salaryMax / salaryCurrency	numbers + ISO code	When the ATS exposes pay bands (Greenhouse + Ashby do)
applyUrl	string	Direct link to the application page
signal (on company_signal)	enum	The dominant intent tag, or general-hiring / shrinking / stable
vendorHypothesis	array	Top 8 vendors aggregated across the company's open roles
changeType (on change_event)	enum	role-opened | role-closed | role-updated | salary-changed

How much does it cost?

Event	Price	Fires when
apify-actor-start	$0.0001	Once per run (per GB of memory)
basic-job-fetched	$0.0015	A normalized job is emitted (modes: jobs)
enriched-job-fetched	$0.008	A Gemini-enriched job is emitted (modes: signals, monitor)
company-signal-event	$0.05	Composite buying signal per company (modes: signals, monitor)
change-event	$0.02	Role opened / closed / updated vs. previous run (modes: monitor, or any mode with incrementalMode)
ats-discovered	$0.005	Domain → ATS detection record (mode: discover)

First 10 chargeable events of every run are free (built-in trial counter — see the run log).

Typical run costs

Scenario	Volume	Cost
Discover ATS for 50 prospects	50 discoveries	$0.25
Pull 50 roles each from 10 companies	500 basic jobs	~$0.75
Weekly signals run, 50 companies × 40 roles	2,000 enriched + 50 signals	~$18.50
Daily monitor, 200 companies × 30 roles, ~3 deltas/co/day	600 changes + 200 signals/day	~$22/day

Comparison: Apollo Pro $99/seat/mo (no signals), ZoomInfo + Bombora $3-5K/mo, Clay Growth $1.5-2.5K/mo, Cognism + intent ~$2K/mo. The 50-company weekly run above costs ~$80/mo — same job-to-be-done, ~5-25× cheaper than every comparable.

Tips & advanced options

• monitor mode is built for scheduling. Set up an Apify schedule (daily or weekly), feed in your prospect list, and only pay for deltas + the latest composite signal. The first run charges full freight (everything is "new"); subsequent runs are deltas-only.
• Workday note — Workday tenants live at tenant.wd{N}.myworkdayjobs.com where N is 1-12. Use workday:tenant.wdN/SiteSegment form. Find the wdN from any URL on their careers page. Some Workday tenants throttle aggressive scraping — switch to RESIDENTIAL proxy if you see 403s.
• Auto-detection covers ~25K-30K companies out of the box (all Greenhouse, Lever, Ashby, SmartRecruiters customers + most Workday F500). For non-detectable domains, pass a direct atsTargets entry and the actor skips resolution.
• Filter aggressively to control budget. functionFilter, seniorityFilter, locationFilter, remoteOnly, postedWithinDays all run before Gemini enrichment, so you only pay enrichment cost on the roles that matter.
• intentBatchSize = 20 is the cost-vs-latency sweet spot. Larger batches cost less per job but increase end-to-end latency.
• Vendor signals are tools/tech mentioned in JDs, not necessarily companies the prospect is buying. A role mentioning "Salesforce" usually means they use Salesforce — sometimes it means they sell to Salesforce customers. Cross-check with intentSummary for context.
• Cross-ATS dedup — if the same company is somehow listed twice (rare), dedup by (atsPlatform, atsSlug) downstream.

Legal & ToS

• Every ATS endpoint used by this actor is publicly published and intended for third-party career-site / aggregator use. No login or API key required.
• Greenhouse Job Board API, Lever Postings API, Ashby Public Job Posting API, and SmartRecruiters Posting API are all explicitly documented as public — see developers.greenhouse.io/job-board, github.com/lever/postings-api, developers.ashbyhq.com/docs/public-job-posting-api, developers.smartrecruiters.com/docs/posting-api.
• Workday CXS endpoints serve the same data as the public-facing careers page; we paginate at default 20-per-page with gentle 150ms pacing.
• The actor is intended for sales intelligence, recruiting research, and market analysis. Do not use the data to discriminate, harass, or auto-apply at scale.
• Job descriptions are © the posting employer. We store and re-emit them verbatim for analysis. Do not republish full JDs as your own content.

FAQ & support

Q: Which ATSes are supported in v1? A: Greenhouse, Lever, Ashby, SmartRecruiters, Workday. BambooHR, Recruitee, Teamtailor, Personio in v1.1.

Q: What's the difference between signals and monitor? A: signals runs the full pipeline every time. monitor does the same but auto-enables incremental mode — on subsequent runs you only see new / changed / closed roles, plus the refreshed company-signal record. Use monitor for scheduled subscriptions.

Q: Why didn't my domain auto-detect? A: ~10-15% of companies use custom careers pages that don't link to a known ATS host. Pass an atsTargets entry directly. Also try the discover mode in isolation — it tells you what was found and what failed.

Q: Can I get LinkedIn / Indeed jobs? A: No. This actor only scrapes companies' own ATS career pages. LinkedIn aggregations are heavily anti-botted and not worth the proxy cost. The data here is fresher anyway — it's the source ATS, not a 2nd-hand index.

Q: Will the intent classifier hallucinate tags? A: The classifier is constrained to a fixed 22-tag taxonomy and instructed to return ["unknown"] if uncertain. We've validated against ~100 real postings; false-positive rate is < 5%. If you see noise, lower the intentBatchSize to 5-8 (smaller context = sharper inference).

Q: How do I report bugs? A: Open an issue on the actor's Apify page. Include the input JSON and the offending record's sourceId + applyUrl.

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