Coveo vs Google Vertex AI: pricing, features and which to choose

Coveo is a Canadian software company listed on the Toronto Stock Exchange under the ticker CVO and led by co-founder and CEO Laurent Simoneau. It sells what it calls an AI-Relevance Platform to large enterprises in four areas: commerce search and product discovery, customer service portals and agent tools, websites, and workplace search for employees. Coveo says more than 700 brands use the platform, and its customer announcements include Palo Alto Networks, Intuit, Deloitte, Boston Scientific and the Australian Taxation Office. Commerce was its fastest growing use case in fiscal 2026, at nearly 60% of new business bookings, with strength among B2B manufacturers and distributors.

The core of Coveo is a unified index that pulls content from more than 30 connectors, including Salesforce, ServiceNow, SharePoint, Confluence, SAP Commerce, Shopify and websites, while respecting each source's permissions. Machine learning models rank results by behavior, recommend products and articles, suggest queries and personalize results for each visitor. Merchandisers and administrators get tools to boost, bury or pin results, run A/B tests and read analytics on searches with no results. Coveo offers prebuilt integrations for Salesforce, including Coveo for Agentforce, plus SAP, Adobe and ServiceNow, and headless libraries for teams that build their own front end. Coveo says customers typically go live in four to six weeks.

Coveo's strengths are deep relevance tuning across many content sources, permission-aware indexing, strong commerce merchandising tools, Salesforce and SAP integrations, and generative answers and an MCP server built on the same index. Its weaknesses are quote-only pricing aimed at large budgets, a setup that usually needs partners or internal search specialists, and more platform than a small site needs. Algolia is a developer-friendly hosted search rival. Elastic offers open search infrastructure to build on. Glean focuses on employee workplace search. Google Vertex AI Search covers search and RAG on Google Cloud. Choose Coveo if you run large commerce or support sites and want AI search tuned for revenue.

Google launched Vertex AI in May 2021 to unify its machine learning services for training, deploying and monitoring models. With the rise of generative AI it became Google Cloud's main platform for enterprises using Gemini and other foundation models, and in 2026 Google began presenting it as the Gemini Enterprise Agent Platform, which its documentation describes as an evolution of Vertex AI. It serves data scientists, machine learning engineers and application developers at companies that run on Google Cloud, who need enterprise security, data residency, governance and integration with BigQuery and other Google data services rather than a consumer API key.

Model Garden offers more than 200 models: Google's Gemini, Imagen, Veo and Chirp models, partner models such as Anthropic's Claude family, and open models such as Gemma and Llama that can be deployed or tuned. Developers prototype prompts in a studio console, ground answers with Google Search or their own data, tune models and evaluate them with the Gen AI evaluation service. RAG Engine connects private data to models, and Vector Search provides a managed vector database. For classic machine learning, Vertex AI still offers custom training on GPUs and TPUs, AutoML, Pipelines, Feature Store, a model registry, monitoring and Colab Enterprise notebooks.

Vertex AI's strengths are first-party access to Gemini, a broad Model Garden including Claude, deep integration with BigQuery and Google Cloud security, a strong open-source agent framework and full MLOps tooling. Its weaknesses are complexity, frequent product renaming, pricing that is hard to forecast and the need for a Google Cloud account and engineering skills. Amazon Bedrock and Azure AI Foundry are the equivalent platforms on AWS and Microsoft Azure. Google AI Studio offers simpler Gemini API access for prototypes. Hugging Face hosts open models, and Databricks suits teams centered on lakehouse data. Choose Vertex AI if your company runs on Google Cloud and needs governed, production AI.