Vectara vs Vertex AI

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Vectara 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 Vectara 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 Vectara and Vertex AI!

Here are some unique insights on Vectara:

Vectara caters to teams that need precision. Its APIs, SDKs, and flexible deployment options (even VPC or on-prem) let you decide exactly how ingestion and retrieval behave. If tweaking search weights and balancing semantic vs. keyword results sounds exciting, Vectara will feel at home.

Just know that the setup and ongoing tuning are a bit heavier than one-size-fits-all tools.

And here's more information on Vertex AI:

No content available.

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

Detailed Feature Comparison

Features
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Vectara
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Vertex AI
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Data Ingestion & Knowledge Sources
  • Pulls in just about any document type—PDF, DOCX, HTML, and more—for a thorough index of your content (Vectara Platform).
  • Packed with connectors for cloud storage and enterprise systems, so your data stays synced automatically.
  • Processes everything behind the scenes and turns it into embeddings for fast semantic search.
  • 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  • Keeps everything current with continuous ingestion and auto-indexing, so your knowledge base never falls out of date.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
  • Robust REST APIs and official SDKs make it easy to drop Vectara into your own apps.
  • Embed search or chat experiences inside websites, mobile apps, or custom portals with minimal fuss.
  • Low-code options—like Azure Logic Apps and PowerApps connectors—keep workflows simple.
  • 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
  • Combines smart vector search with a generative LLM to give context-aware answers.
  • Uses its own Mockingbird LLM to serve answers and cite sources.
  • Keeps track of conversation history and supports multi-turn chats for smooth back-and-forth.
  • 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
  • Full control over look and feel—swap themes, logos, CSS, you name it—for a true white-label vibe.
  • Restrict the bot to specific domains and tweak branding straight from the config.
  • Even the search UI and result cards can be styled to match your company identity.
  • 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 its in-house Mockingbird model by default, but can call GPT-4 or GPT-3.5 through Azure OpenAI.
  • Lets you choose the model that balances cost versus quality for your needs.
  • Prompt templates are customizable, so you can steer tone, format, and citation rules.
  • 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)
  • Comprehensive REST API plus SDKs for C#, Python, Java, and JavaScript (Vectara FAQs).
  • Clear docs and sample code walk you through integration and index ops.
  • Secure API access via Azure AD or your own auth setup.
  • 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
  • Plugs into Azure services like Logic Apps and Power BI for end-to-end automation.
  • Low-code connectors and REST endpoints drop search and chat into any custom app.
  • APIs let you wire Vectara into CRM, ERP, or ticketing systems for bespoke workflows.
  • 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
  • Tuned for enterprise scale—expect millisecond responses even with heavy traffic (Microsoft Mechanics).
  • Hybrid search blends semantic and keyword matching for pinpoint accuracy.
  • Advanced reranking and a factual-consistency score keep hallucinations in check.
  • 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-grain control over indexing—set chunk sizes, metadata tags, and more.
  • Tune how much weight semantic vs. lexical search gets for each query.
  • Adjust prompt templates and relevance thresholds to fit domain-specific needs.
  • 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
  • Usage-based pricing with a healthy free tier—bigger bundles available as you grow (Bundle pricing).
  • Plans scale smoothly with query volume and data size, plus enterprise tiers for heavy hitters.
  • Need isolation? Go with a dedicated VPC or on-prem deployment.
  • 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
  • Encrypts data in transit and at rest—and never trains external models with your content.
  • Meets SOC 2, ISO, GDPR, HIPAA, and more (see Azure Compliance).
  • Supports customer-managed keys and private deployments for full control.
  • 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
  • Azure portal dashboard tracks query latency, index health, and usage at a glance.
  • Hooks into Azure Monitor and App Insights for custom alerts and dashboards.
  • Export logs and metrics via API for deep dives or compliance reports.
  • 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
  • Backed by Microsoft’s support network, with docs, forums, and technical guides.
  • Enterprise plans add dedicated channels and SLA-backed help.
  • Benefit from the broad Azure partner ecosystem and vibrant dev community.
  • 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
  • Hybrid search + reranking gives each answer a unique factual-consistency score.
  • Deploy in public cloud, VPC, or on-prem to suit your compliance needs.
  • Constant stream of new features and integrations keeps the platform fresh.
  • 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
  • Azure portal UI makes managing indexes and settings straightforward.
  • Low-code connectors (PowerApps, Logic Apps) help non-devs integrate search quickly.
  • Complex indexing tweaks may still need a tech-savvy hand compared with turnkey tools.
  • 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 Vectara vs Vertex AI helpful.

Vectara’s depth and enterprise-grade features are a big win when you need custom deployments. If you’re after a fast, plug-and-play experience, be ready for extra configuration work.

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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.