Vertex AI Search
Site search software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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Pay-as-you-go
Free Trial
Free version unavailable
Small
Medium
Large
- Banking and insurance
- Construction
- Healthcare and life sciences
What is Vertex AI Search
Vertex AI Search is a Google Cloud managed search service that helps organizations build search experiences over websites, apps, and enterprise content sources. It is used by product teams and developers to implement relevance tuning and semantic retrieval without operating their own search infrastructure. The service integrates with Google Cloud data connectors and can incorporate generative AI features for query understanding and answer-style results. It is typically adopted by teams already standardizing on Google Cloud and Vertex AI services.
Managed, cloud-native operations
Vertex AI Search is delivered as a managed service, reducing the need to provision clusters, manage scaling, or handle patching compared with self-managed search stacks. It fits common Google Cloud operational patterns for IAM, monitoring, and billing. This can shorten time-to-production for teams that do not want to run search infrastructure. It also supports production use cases where reliability and operational consistency matter.
Semantic and generative retrieval
The product supports semantic search capabilities that go beyond keyword matching, which can improve retrieval for natural-language queries. It can be used to power answer-style experiences by combining retrieval with generative AI features in the Google Cloud ecosystem. This is useful for support portals, documentation sites, and internal knowledge search where users ask questions rather than type exact terms. Teams can implement these capabilities without assembling multiple separate components.
Google Cloud ecosystem integration
Vertex AI Search integrates with Google Cloud services and data sources, which can simplify ingestion and security for organizations already using Google Cloud. It aligns with Google Cloud identity and access controls, helping centralize governance. It also benefits teams that want a single vendor for search, AI, and hosting. This reduces integration work compared with stitching together separate search and AI services.
Google Cloud lock-in risk
The service is tightly coupled to Google Cloud, which can increase switching costs if an organization later moves to another cloud or on-prem environment. Data ingestion, security configuration, and AI features often rely on Google Cloud-native components. This can limit portability compared with open-source or cloud-agnostic search stacks. Procurement and governance may also require alignment with Google Cloud contracts.
Less low-level search control
Teams that need deep control over indexing internals, custom analyzers, or bespoke ranking pipelines may find fewer low-level knobs than in self-managed search engines. Some advanced tuning can be constrained by the managed abstraction and available configuration surfaces. This can matter for highly specialized e-commerce or domain-specific retrieval requirements. In those cases, engineering teams may prefer systems that expose more of the underlying search engine behavior.
Cost and usage complexity
Pricing can be harder to predict because costs may depend on indexing volume, query traffic, and optional AI features. Organizations may need to monitor usage closely to avoid unexpected spend, especially when enabling generative experiences. Budget owners may also need to account for adjacent Google Cloud services used for ingestion and hosting. This can be more complex than a fixed-license or self-hosted approach where infrastructure costs are directly controlled.
Plan & Pricing
Product: Vertex AI Search (Google Cloud)
Pricing models:
- General Pricing (Pay-as-you-go) Pricing model: Pay-as-you-go Free tier/trial: 10,000 queries per account, per month at no cost (excludes Advanced Generative Answers). 10 GiB index storage free quota per month. Query pricing (per 1,000 queries):
- Search Standard Edition: $1.50 / 1,000 queries
- Search Enterprise Edition (includes Core Generative Answers / AI Mode): $4.00 / 1,000 queries
- Advanced Generative Answers (AI Mode) add-on: +$4.00 / 1,000 user-input queries (can be added to Standard or Enterprise) Index storage: $5.00 / GiB of raw data per month (10 GiB free quota) Special SKU: Vertex AI Search for Healthcare: $20.00 / 1,000 queries Notes: Example and calculations shown on the official pricing page. Overages or additional features referenced on the official site.
- Configurable Pricing (Monthly subscription + optional pay-as-you-go add-ons) Pricing model: Monthly subscription (core capacity) with pay-as-you-go add-ons Minimum monthly commitment: 1,000 QPM (queries per minute) and 50 GB storage (minimum commitment stated on official site) Core subscription (billed monthly):
- Query Unit: $6.00 / QPM / month
- Storage Unit: $1.00 / GB / month Pay-as-you-go add-ons (billed per 1,000 queries unless noted):
- Semantic: $0.75 / 1,000 queries + $1.50 / GB / month for embeddings (additional storage charge for embeddings)
- KPI & Personalization: $0.20 / 1,000 queries
- Core Generative Answers: $2.00 / 1,000 queries (requires Semantic add-on)
- Advanced Generative Answers (AI Mode): $4.00 / 1,000 queries (requires Semantic add-on) Index storage (Configurable): storage subscription applies ($1 / GB / month core storage + any embedding storage for Semantic add-on as applicable) Overages: Queries beyond subscribed QPM are billed at General Pricing Standard Edition rate ($1.50 / 1,000 queries) by default.
Additional notes / examples: The official pricing page includes worked examples (Document Search, Hotel Search) and details on how index storage is calculated (e.g., website pages estimated at ~500 KiB per page).
Seller details
Google LLC
Mountain View, CA, USA
1998
Subsidiary
https://cloud.google.com/deep-learning-vm
https://x.com/googlecloud
https://www.linkedin.com/company/google/
