Supavec vs Vertex AI

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Supavec 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 Supavec 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 Supavec and Vertex AI!

Here are some unique insights on Supavec:

Supavec is an open-source RAG API for devs who want full control. Upload PDFs, Markdown, or raw text via REST and build your own connectors for other data. Flexibility is high, but you’ll write more code—there’s no one-click Google Drive or Notion sync.

The upside: you own the stack. The trade-off: extra scripting and a lack of a polished no-code UI.

And here's more information on Vertex AI:

No content available.

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

Detailed Feature Comparison

Features
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Supavec
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Vertex AI
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Data Ingestion & Knowledge Sources
  • Drop content in via REST: upload PDFs, Markdown, or TXT [Upload File] or send raw text [Upload Text].
  • No one-click Google Drive or Notion connectors—you’ll script the fetch and hit the API yourself.
  • Because it’s open source, you can build connectors to anything—Postgres, Mongo, S3, you name it.
  • Runs on Supabase and scales sideways, chunking millions of docs for fast retrieval.
  • 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  • Keeps everything current with continuous ingestion and auto-indexing, so your knowledge base never falls out of date.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
  • Pure REST for retrieval and generation—no built-in widget or Slack bot.
  • You code the chat UI or Slack bridge, calling Supavec for answers.
  • No Zapier—webhooks and automations are DIY inside your app.
  • If it speaks HTTP, it can talk to Supavec—you just handle the front-end.
  • 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
  • Just the essentials: retrieve chunks + LLM answer. Calls are stateless, no baked-in chat history.
  • No lead capture or human handoff—add those in your own layer.
  • Pulls the right text fast, then lets your LLM craft the reply.
  • Perfect if you only need raw RAG and will build the conversation bits yourself.
  • 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
  • No pre-made UI, no theming—branding lives in whatever front-end you create.
  • Open source means zero “Supavec” label to hide—your app, your look.
  • Add domain checks or auth however you like in your code.
  • It’s “white-label” by default because Supavec is API-only.
  • 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
  • Model-agnostic: defaults to GPT-3.5, but switch to GPT-4 or any self-hosted model if you’d like.
  • No fancy toggle—just change a config or prompt path in code.
  • No extra prompt magic or anti-hallucination layer—plain RAG.
  • Quality rests on the LLM you choose and how you prompt it.
  • 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)
  • Straightforward REST endpoints for file uploads, text uploads, and search. [Examples]
  • No official SDKs—use fetch/axios or roll your own wrapper.
  • Docs are concise with JS snippets; Postman collection included.
  • Full source is on GitHub, welcoming community tweaks.
  • 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
  • Think of it as a Lego brick: upload content, query matches, feed results to your LLM.
  • No built-in triggers—external actions are on you.
  • Scale horizontally on Supabase when self-hosted, or use the hosted plan (with API-call limits).
  • Big orgs can chat about higher tiers or dedicated infra for heavy traffic.
  • 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
  • Accuracy = GPT quality + standard RAG lift—no extra guardrails.
  • Postgres vector search keeps retrieval snappy, even with millions of chunks.
  • No public head-to-head benchmarks yet; expect “typical GPT-3.5/4 RAG” results.
  • If you want citations or extra checks, you’ll prompt-engineer them yourself.
  • 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)
  • Upload or overwrite docs any time—re-embeds almost instantly.
  • Behavior lives in your prompts; there’s no GUI for personas.
  • Multi-lingual works fine—just tell the LLM in your prompt.
  • Add metadata, tweak chunking—then build logic around it as needed.
  • 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
  • MIT-licensed open source: self-host for free (pay your own infra).
  • Hosted plans: Free (100 calls/mo), Basic $190/yr (750 calls/mo), Enterprise $1,490/yr (5 k calls/mo). [Pricing]
  • Need more calls? Negotiate or self-host to ditch caps.
  • Storage isn’t metered—only query volume counts toward the plan.
  • 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
  • Self-hosting keeps everything on your servers—great for tight compliance. [Privacy note]
  • Hosted Supavec runs on Supabase with row-level security—each team’s data is fenced off.
  • No training on your docs—data stays yours.
  • Enterprises can go dedicated or on-prem for HIPAA/GDPR peace of mind.
  • 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
  • No dashboard baked in—log requests yourself or use Supabase metrics when self-hosting.
  • Hosted plan shows basic call counts; no transcript analytics out of the box.
  • Need deep insights? Wire up your own monitoring layer.
  • Designed to play nicely with external logging tools, not ship its own.
  • 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
  • Community help via GitHub/Discord; paid plans unlock email or priority support. [Docs]
  • Open-source means forks, PRs, and home-grown connectors are welcome.
  • Docs are lean—mostly endpoint references rather than big tutorials.
  • Code samples pop up in the community, but it’s not a huge library yet.
  • 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
  • No vendor lock-in: transparent code, offline option, host wherever you like.
  • Focuses on core RAG—no SSO, dashboards, or fancy UI included.
  • Great for devs who want full control or must keep data in-house.
  • Conversation flow, advanced prompts, fancy UI—all yours to build.
  • 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
  • No drag-and-drop dashboard—everything’s via API or CLI.
  • Meant for code-first teams who’ll bolt it into their own chat or workflow.
  • Self-hosters can craft custom GUIs on top, but Supavec keeps the slate blank.
  • If you want a business-user UI like CustomGPT, you’ll layer that yourself.
  • 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 Supavec vs Vertex AI helpful.

Supavec is perfect when you value transparency and control over convenience. If you’d rather avoid extra coding and maintenance, a managed, plug-and-play platform may be a better fit.

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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.