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Side-by-side record

Google Vertex AI vs. Greenhouse

A side-by-side view of the product records we have today. Use it to narrow the question, then confirm current pricing, limits, and security details with each vendor.

The short version

Google Vertex AI starts at Free per seat, versus Greenhouse at Custom pricing. Google Vertex AI carries the higher aggregate rating (9.6/5 vs 4.4/5).

Full comparison

Google Vertex AIfrom Free
Greenhousefrom Custom pricing
Audyense Score29AS*Low71ASStrong
PositioningGoogle Vertex AI is a powerful platform that signifies Google’s unwavering commitment to advancing the field of artificial intelligence.Structured-hiring applicant tracking and recruiting platform for consistent, data-driven hiring at scale
Free tierYesNo
DeploymentCloud / SaaSCloud / SaaS
Best fitStartup, SMB, Mid-marketMid-market, Enterprise
Pricing plans
  • Free or entry planFree
  • Higher tiersCustom pricing
  • CoreCustom pricing
  • PlusCustom pricing
  • ProCustom pricing
AutoML CapabilitiesYesDocumented in the independently researched profile.—
Custom Model DevelopmentYesDocumented in the independently researched profile.—
Pre-built ModelsYesDocumented in the independently researched profile.—
Model Deployment and MonitoringYesDocumented in the independently researched profile.—
Model Versioning and ManagementYesDocumented in the independently researched profile.—
Real-time PredictionsYesDocumented in the independently researched profile.—
Custom Training ContainersYesDocumented in the independently researched profile.—
Multi-Cloud DeploymentYesDocumented in the independently researched profile.—
AI ExplanationsYesDocumented in the independently researched profile.—
Data Labeling Services IntegrationYesDocumented in the independently researched profile.—
Jupyter NotebooksYesDocumented in the independently researched profile.—
AI for Multiple Data TypesYesDocumented in the independently researched profile.—
Model Hyperparameter TuningYesDocumented in the independently researched profile.—
Custom Training Jobs.YesDocumented in the independently researched profile.—
Applicant tracking (ATS)—YesCore product: full ATS with structured hiring, pipelines, and scorecards.
Benefits administration—NoNot a benefits platform; handled via HRIS integrations.
Employee directory & org chart—NoFocused on candidates and hiring, not an employee directory.
Mobile app—PartialMobile apps for recruiters and interviewers, but not the primary interface.
Employee onboarding—PartialAvailable via a separate Greenhouse Onboarding product, not the core ATS.
Payroll—NoNo payroll; relies on HRIS/payroll integrations.
Performance reviews—NoNot a performance-management tool.
Public API—YesOpen/public API plus a 450+ integration marketplace.
Reporting & dashboards—PartialBuilt-in reporting exists but reviewers cite limited customization and slow refresh.
Time-off & PTO management—NoNo time-off or PTO management.
Integrations verified—500+
Aggregate rating9.6 · No reviews yet4.4 · 3.8k reviews
Integrations—
LinkedIn RecruiterIndeedGemHackerRankCodilityCheckr+9 more
Security & compliance—
SOC 1 Type IISOC 2 Type IIISO 27001ISO 27701+3 more
Pros
  • Independent review documents a concrete business workflow
  • Documented capability: AutoML Capabilities
  • Documented capability: Custom Model Development
  • Documented capability: Pre-built Models
  • Documented capability: Model Deployment and Monitoring
  • Structured interview kits and candidate scorecards drive consistent, fairer hiring decisions
  • Intuitive, easy-to-learn interface that new hiring-team members onboard onto quickly
  • Large integration ecosystem (450+ partners) plus an open API for building a custom stack
  • Scales effectively for fast-growing small-to-enterprise organizations
Cons
  • Pricing and usage limits should be checked against the exact plan
  • Implementation effort depends on the team's data and process maturity
  • Reported outcomes should be validated with the buyer's own data
  • Reporting and analytics are seen as limited and harder to customize, and dashboards can be slow to refresh
  • Pricing is undisclosed and considered too expensive for smaller companies
  • Navigation and some workflows can feel clunky
  • Support is largely email-based and can be hard to reach live
Visit Google Vertex AI ↗Visit Greenhouse ↗

Editorial read of this comparison

The table summarizes structured facts; this section explains what the differences mean for a real buying decision.

Where each tool fits, and where it may not

Google Vertex AI

Google Vertex AI is a powerful platform that signifies Google’s unwavering commitment to advancing the field of artificial intelligence. It’s designed to simplify and optimize the entire process of building and deploying machine learning models, making AI accessible to a broader range of users while also providing tools for experts to create customized solutions. This platform offers a unified environment where data preparation, model development, and model deployment are seamlessly integrated, offering a holistic approach to AI development. One of the standout features of Google Vertex AI is its AutoML capabilities. These tools cater to users with varying levels of expertise, allowing them to build AI models without the need for deep technical knowledge. Whether it’s image recognition, natural language processing, or structured data analysis, AutoML simplifies model creation, democratizing AI by empowering business professionals and data enthusiasts to harness its power. For those with more specialized needs, Google Vertex AI supports custom model development. It enables data scientists and machine learning engineers to work with popular deep learning frameworks such as TensorFlow and PyTorch, providing a high degree of flexibility to craft models tailored to specific use cases. This duality in approach, accommodating both novices and experts, makes Vertex AI an inclusive platform that can cater to diverse user profiles. Vertex AI’s seamless integration with other Google Cloud services is another noteworthy feature. This integration guarantees scalability and reliability, as organizations can tap into Google Cloud’s robust infrastructure, data storage, and analytics tools. As AI solutions grow in complexity and data volumes increase, this cohesive environment ensures that AI models can evolve to meet the demands of real-world application

A particularly good fit for: B2B teams evaluating HR and People software Teams that need documented workflow capabilities and fit guidance Organizations willing to validate implementation and plan limits

May be a poor fit if: Teams seeking a workflow outside the product's documented focus Teams needing unlimited usage without plan limits

Greenhouse

Greenhouse is a cloud-based applicant tracking system (ATS) and recruiting platform built around structured hiring, using standardized interview kits, scorecards, and sourcing/CRM tools to make hiring consistent and data-driven. Founded in 2012 and headquartered in New York, it serves thousands of companies from mid-market to enterprise. It offers a large partner ecosystem plus an open API, and a separate Onboarding product. Pricing is quote-based, tiered by hiring volume and organizational complexity.

A particularly good fit for: Mid-market and enterprise talent teams that want consistent, structured, data-driven hiring processes Rapidly scaling companies needing an ATS that grows with hiring volume and headcount Tech-forward recruiting teams that rely on many integrations for sourcing, assessments, background checks, and HRIS

May be a poor fit if: Small businesses or startups on tight budgets, given opaque quote-based pricing and no free trial Teams that need deeply customizable, real-time reporting out of the box

Pricing and plan structure

Google Vertex AI: Published starting price Free

  • Free or entry planFree
  • Higher tiersCustom pricing

Greenhouse: Published starting price Custom pricing

  • CoreCustom pricing
  • PlusCustom pricing
  • ProCustom pricing

Capabilities worth validating

  • Google Vertex AI: AutoML Capabilities, Custom Model Development, Pre-built Models, Model Deployment and Monitoring, Model Versioning and Management
  • Greenhouse: Applicant tracking (ATS), Mobile app, Employee onboarding, Public API, Reporting & dashboards Integrations include LinkedIn Recruiter, Indeed, Gem, HackerRank.

Questions to answer before switching

  • Does Google Vertex AI's selected plan include the features and limits we need?
  • Does Greenhouse's selected plan include the features and limits we need?
  • Does the exact integration path for LinkedIn Recruiter, Indeed, Gem support the sync direction, permissions, and volume we need?
  • Is a hosted-only deployment acceptable for the team and customers who will use this system?

How to evaluate this shortlist

A useful comparison turns the differences between HR & People tools into a concrete test. Use these steps to avoid choosing from a feature table or the lowest headline price alone.

  1. Start with a representative HR & People workflow, not a feature checklist. Define who will use it, what data goes in, and what outcome the team needs.
  2. Test the complete path through LinkedIn Recruiter, Indeed, Gem: permissions, sync direction, failure handling, and volume limits often matter more than the integration name.
  3. Compare the cost of the real scenario, including users, usage, storage, support, and contract requirements. The entry price alone does not measure adoption cost.
  4. Before switching, list the evidence gaps, request a demo of the critical workflow, and confirm security, data residency, export, and support with each vendor.

Structured signals help narrow the shortlist, but a trial with a real workflow is still the best way to validate the decision.

Research basis

Last checked: 2026-08-18. Pricing, integrations, feature support, and review signals can change, so treat this as a research snapshot and verify the final decision with the vendor.

Sources consulted: Google Vertex AI product site, FinancesOnline review, Vendor website; Greenhouse product site, G2, Capterra