Coveo vs Vertex AI

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Coveo vs Vertex AI Comparison
Priyansh Khodiyar's avatar
Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare Coveo and Vertex AI across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.

Overview

Welcome to the comparison between Coveo and Vertex AI!

Here are some unique insights on Coveo:

Coveo adds RAG features to its enterprise search platform, folding AI answers into a unified index of SharePoint, Salesforce, file shares, and more. It’s powerful, especially with built-in permission filters, but setup targets larger orgs that already rely on Coveo for search.

And here's more information on Vertex AI:

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Enjoy reading and exploring the differences between Coveo and Vertex AI.

Detailed Feature Comparison

Features
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Coveo
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Vertex AI
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Data Ingestion & Knowledge Sources
  • Pulls content from a long list of enterprise sources—SharePoint, Salesforce, ServiceNow, Confluence, databases, file shares, Slack, websites—and merges it all into one index with native connectors.
  • Runs OCR and handles structured data, so it can index scanned docs, intranet pages, knowledge articles, and even multimedia.
  • Keeps the index fresh with incremental crawls, push APIs, and scheduled syncs—new or updated content shows up fast.
  • Pulls in both structured and unstructured data straight from Google Cloud Storage, handling files like PDF, HTML, and CSV (Vertex AI Search Overview).
  • Taps into Google’s own web-crawling muscle to fold relevant public website content into your index with minimal fuss (Towards AI Vertex AI Search).
  • Keeps everything current with continuous ingestion and auto-indexing, so your knowledge base never falls out of date.
  • Lets you ingest more than 1,400 file formats—PDF, DOCX, TXT, Markdown, HTML, and many more—via simple drag-and-drop or API.
  • Crawls entire sites through sitemaps and URLs, automatically indexing public help-desk articles, FAQs, and docs.
  • Turns multimedia into text on the fly: YouTube videos, podcasts, and other media are auto-transcribed with built-in OCR and speech-to-text. View Transcription Guide
  • Connects to Google Drive, SharePoint, Notion, Confluence, HubSpot, and more through API connectors or Zapier. See Zapier Connectors
  • Supports both manual uploads and auto-sync retraining, so your knowledge base always stays up to date.
Integrations & Channels
  • Ships Atomic UI components you can drop into search pages, support hubs, or commerce sites to surface generative answers.
  • Connects natively to platforms like Salesforce and Sitecore, letting AI answers appear right inside tools your team already uses.
  • Need a custom channel? Its robust REST APIs let you build bespoke chatbots or virtual assistants on top of Coveo’s retrieval engine.
  • Ships solid REST APIs and client libraries for weaving Vertex AI into web apps, mobile apps, or enterprise portals (Google Cloud Vertex AI API Docs).
  • Plays nicely with other Google Cloud staples—BigQuery, Dataflow, and more—and even supports low-code connectors via Logic Apps and PowerApps (Google Cloud Connectors).
  • Lets you deploy conversational agents wherever you need them, whether that’s a bespoke front-end or an embedded widget.
  • Embeds easily—a lightweight script or iframe drops the chat widget into any website or mobile app.
  • Offers ready-made hooks for Slack, Microsoft Teams, WhatsApp, Telegram, and Facebook Messenger. Explore API Integrations
  • Connects with 5,000+ apps via Zapier and webhooks to automate your workflows.
  • Supports secure deployments with domain allowlisting and a ChatGPT Plugin for private use cases.
Core Chatbot Features
  • Uses Relevance Generative Answering (RGA)—a two-step retrieval plus LLM flow that produces concise, source-cited answers.
  • Respects permissions, showing each user only the content they’re allowed to see.
  • Blends the direct answer with classic search results so people can dig deeper if they want.
  • Pairs Vertex AI Search with Vertex AI Conversation to craft answers grounded in your indexed data (Google Developers Blog Vertex AI RAG).
  • Draws on Google’s PaLM 2 or Gemini models for rich, context-aware responses.
  • Handles multi-turn dialogue and keeps track of context so chats stay coherent.
  • Powers retrieval-augmented Q&A with GPT-4 and GPT-3.5 Turbo, keeping answers anchored to your own content.
  • Reduces hallucinations by grounding replies in your data and adding source citations for transparency. Benchmark Details
  • Handles multi-turn, context-aware chats with persistent history and solid conversation management.
  • Speaks 90+ languages, making global rollouts straightforward.
  • Includes extras like lead capture (email collection) and smooth handoff to a human when needed.
Customization & Branding
  • Atomic components are fully styleable with CSS, making it easy to match your brand’s look and feel.
  • You can tweak answer formatting and citation display through configs; deeper personality tweaks mean editing the prompt.
  • Lets you tweak UI elements in the Cloud console so your chatbot matches your brand style.
  • Includes settings for custom themes, logos, and domain restrictions when you embed search or chat (Google Cloud Console).
  • Makes it easy to keep branding consistent by tying into your existing design system.
  • Fully white-labels the widget—colors, logos, icons, CSS, everything can match your brand. White-label Options
  • Provides a no-code dashboard to set welcome messages, bot names, and visual themes.
  • Lets you shape the AI’s persona and tone using pre-prompts and system instructions.
  • Uses domain allowlisting to ensure the chatbot appears only on approved sites.
L L M Model Options
  • Runs primarily on OpenAI GPT models via Azure OpenAI, delivering high-quality text.
  • If you prefer another model, the Relevance-Augmented Passage Retrieval API lets you plug in your own LLM.
  • Handles model tuning and prompt optimization behind the scenes, though you can override via API when needed.
  • Connects to Google’s own generative models—PaLM 2, Gemini—and can call external LLMs via API if you prefer (Google Cloud Vertex AI Models).
  • Lets you pick models based on your balance of cost, speed, and quality.
  • Supports prompt-template tweaks so you can steer tone, format, and citation rules.
  • Taps into top models—OpenAI’s GPT-4, GPT-3.5 Turbo, and even Anthropic’s Claude for enterprise needs.
  • Automatically balances cost and performance by picking the right model for each request. Model Selection Details
  • Uses proprietary prompt engineering and retrieval tweaks to return high-quality, citation-backed answers.
  • Handles all model management behind the scenes—no extra API keys or fine-tuning steps for you.
Developer Experience ( A P I & S D Ks)
  • Provides mature REST APIs and SDKs (Java, .NET, JavaScript) for indexing, connector management, and querying.
  • Ready-made Atomic and Quantic components help you add generative answers to the front end fast.
  • Docs are enterprise-grade, with step-by-step guides for pipelines and index management.
  • Offers full REST APIs plus client libraries for Python, Java, JavaScript, and more (Google Cloud Vertex AI SDK).
  • Backs you up with rich docs, sample notebooks, and quick-start guides.
  • Uses Google Cloud IAM for secure API calls and supports CLI tooling for local dev work.
  • Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat. API Documentation
  • Offers open-source SDKs—like the Python customgpt-client—plus Postman collections to speed integration. Open-Source SDK
  • Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
Integration & Workflow
  • Slots into enterprise workflows by indexing multiple systems without moving the data.
  • Incremental indexing and push updates mean new content is searchable almost immediately.
  • Generative answer widgets can be embedded wherever you need a unified search experience.
  • Snaps into other GCP services—BigQuery, Dataflow, Cloud Functions—for end-to-end workflows (Google Cloud Architecture).
  • Follows a modular, API-driven design so you can mix search and chat components the way you want.
  • Automates tasks via connectors or custom code to tie into CRMs, ticketing tools, and beyond.
  • Gets you live fast with a low-code dashboard: create a project, add sources, and auto-index content in minutes.
  • Fits existing systems via API calls, webhooks, and Zapier—handy for automating CRM updates, email triggers, and more. Auto-sync Feature
  • Slides into CI/CD pipelines so your knowledge base updates continuously without manual effort.
Performance & Accuracy
  • Pairs keyword search with semantic vector search so the LLM gets the best possible context.
  • Reranking plus smart prompts keep hallucinations low and citations precise.
  • Built on a scalable architecture that handles heavy query loads and massive content sets.
  • Serves answers in milliseconds thanks to Google’s global infrastructure (Google Cloud Vertex AI RAG).
  • Combines semantic and keyword search for strong retrieval accuracy.
  • Adds advanced reranking to cut hallucinations and keep facts straight.
  • Delivers sub-second replies with an optimized pipeline—efficient vector search, smart chunking, and caching.
  • Independent tests rate median answer accuracy at 5/5—outpacing many alternatives. Benchmark Results
  • Always cites sources so users can verify facts on the spot.
  • Maintains speed and accuracy even for massive knowledge bases with tens of millions of words.
Customization & Flexibility ( Behavior & Knowledge)
  • Fine-tune which sources and metadata the engine uses via query pipelines and filters.
  • Integrates with SSO/LDAP so results are tailored to each user’s permissions.
  • Developers can tweak prompt templates or inject business rules to shape the output.
  • Gives fine-grained control over indexing—set chunk sizes, metadata tags, and more to shape retrieval (Google Cloud Vertex AI Search).
  • Lets you adjust generation knobs (temperature, max tokens) and craft prompt templates for domain-specific flair.
  • Can slot in custom cognitive skills or open-source models when you need specialized processing.
  • Lets you add, remove, or tweak content on the fly—automatic re-indexing keeps everything current.
  • Shapes agent behavior through system prompts and sample Q&A, ensuring a consistent voice and focus. Learn How to Update Sources
  • Supports multiple agents per account, so different teams can have their own bots.
  • Balances hands-on control with smart defaults—no deep ML expertise required to get tailored behavior.
Pricing & Scalability
  • Sold under enterprise licenses—pricing depends on sources, query volume, and feature set.
  • Scales to millions of queries with 99.999 % uptime and regional data-center options.
  • Usually involves annual contracts with volume tiers and optional premium support.
  • Uses pay-as-you-go pricing—charges for storage, query volume, and model compute—with a free tier to experiment (Google Cloud Pricing).
  • Scales effortlessly on Google’s global backbone, with autoscaling baked in.
  • Add partitions or replicas as traffic grows to keep performance rock-solid.
  • Runs on straightforward subscriptions: Standard (~$99/mo), Premium (~$449/mo), and customizable Enterprise plans.
  • Gives generous limits—Standard covers up to 60 million words per bot, Premium up to 300 million—all at flat monthly rates. View Pricing
  • Handles scaling for you: the managed cloud infra auto-scales with demand, keeping things fast and available.
Security & Privacy
  • Holds ISO 27001/27018 and SOC 2 certifications, plus HIPAA-compatible deployments.
  • Granular access controls ensure users only see what they’re authorized to view.
  • Can run in private cloud or on-prem for organizations with strict data-residency needs.
  • Builds on Google Cloud’s security stack—encryption in transit and at rest, plus fine-grained IAM (Google Cloud Compliance).
  • Holds a long list of certifications (SOC, ISO, HIPAA, GDPR) and supports customer-managed encryption keys.
  • Offers options like Private Link and detailed audit logs to satisfy strict enterprise requirements.
  • Protects data in transit with SSL/TLS and at rest with 256-bit AES encryption.
  • Holds SOC 2 Type II certification and complies with GDPR, so your data stays isolated and private. Security Certifications
  • Offers fine-grained access controls—RBAC, two-factor auth, and SSO integration—so only the right people get in.
Observability & Monitoring
  • Built-in analytics dashboard tracks query volume, engagement, and generative-answer performance.
  • Detailed pipeline logs can be exported for deeper analysis.
  • Supports A/B testing in the query pipeline to measure impact and fine-tune relevance.
  • Hooks into Google Cloud Operations Suite for real-time monitoring, logging, and alerting (Google Cloud Monitoring).
  • Includes dashboards for query latency, index health, and resource usage, plus APIs for custom analytics.
  • Lets you export logs and metrics to meet compliance or deep-dive analysis needs.
  • Comes with a real-time analytics dashboard tracking query volumes, token usage, and indexing status.
  • Lets you export logs and metrics via API to plug into third-party monitoring or BI tools. Analytics API
  • Provides detailed insights for troubleshooting and ongoing optimization.
Support & Ecosystem
  • Comes with enterprise-grade support—account managers, 24/7 help, and extensive training programs.
  • Large partner network and the Coveo Connect community provide docs, forums, and certified integrations.
  • Regular product updates and industry events keep you ahead of the curve.
  • Backed by Google’s enterprise support programs and detailed docs across the Cloud platform (Google Cloud Support).
  • Provides community forums, sample projects, and training via Google Cloud’s dev channels.
  • Benefits from a robust ecosystem of partners and ready-made integrations inside GCP.
  • Supplies rich docs, tutorials, cookbooks, and FAQs to get you started fast. Developer Docs
  • Offers quick email and in-app chat support—Premium and Enterprise plans add dedicated managers and faster SLAs. Enterprise Solutions
  • Benefits from an active user community plus integrations through Zapier and GitHub resources.
Additional Considerations
  • Coveo goes beyond Q&A to power search, recommendations, and discovery for large digital experiences.
  • Deep integration with enterprise systems and strong permissioning make it ideal for internal knowledge management.
  • Powerful but best suited for organizations with an established IT team to tune and maintain it.
  • Packs hybrid search and reranking that return a factual-consistency score with every answer.
  • Supports public cloud, VPC, or on-prem deployments if you have strict data-residency rules.
  • Gets regular updates as Google pours R&D into RAG and generative AI capabilities.
  • Slashes engineering overhead with an all-in-one RAG platform—no in-house ML team required.
  • Gets you to value quickly: launch a functional AI assistant in minutes.
  • Stays current with ongoing GPT and retrieval improvements, so you’re always on the latest tech.
  • Balances top-tier accuracy with ease of use, perfect for customer-facing or internal knowledge projects.
No- Code Interface & Usability
  • Admin console and Atomic components let you get started with minimal code.
  • The end-user search UI is polished, but full generative setup usually calls for developer involvement.
  • Great for teams that already have technical resources or use Coveo today; more complex than a pure no-code tool.
  • Offers a Cloud console to manage indexes and search settings, though there’s no full drag-and-drop chatbot builder yet.
  • Low-code connectors (PowerApps, Logic Apps) make basic integrations straightforward for non-devs.
  • The overall experience is solid, but deeper customization still calls for some technical know-how.
  • Offers a wizard-style web dashboard so non-devs can upload content, brand the widget, and monitor performance.
  • Supports drag-and-drop uploads, visual theme editing, and in-browser chatbot testing. User Experience Review
  • Uses role-based access so business users and devs can collaborate smoothly.

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Final Thoughts

We hope you found this comparison of Coveo vs Vertex AI helpful.

If robust search plus AI answers across many touchpoints is your goal—and you have the resources for a fuller implementation—Coveo is worth exploring. For a quick standalone chatbot, its breadth could be more than you need.

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Priyansh Khodiyar's avatar

Priyansh Khodiyar

DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.