In this comprehensive guide, we compare Botpress and Supavec across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.
Overview
When choosing between Botpress and Supavec, understanding their unique strengths and architectural differences is crucial for making an informed decision. Both platforms serve the RAG (Retrieval-Augmented Generation) space but cater to different use cases and organizational needs.
Quick Decision Guide
Choose Botpress if: you value visual drag-and-drop builder with extensive code extensibility via execute code cards
Choose Supavec if: you value 100% open source with no vendor lock-in
About Botpress
Botpress is enterprise ai agent platform with visual bot building and omnichannel deployment. Enterprise AI agent platform with visual bot building, omnichannel deployment, and RAG capabilities. 750,000+ active bots processing 1 billion+ messages with extensive channel support and no-code/low-code development. Founded in 2016, headquartered in Montreal, Quebec, Canada, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
85/100
Starting Price
Custom
About Supavec
Supavec is the open source rag as a service platform. SupaVec is an open-source RAG platform that serves as an alternative to Carbon.ai. Built on transparency and data sovereignty, it allows developers to build powerful RAG applications with complete control over their infrastructure, supporting any data source at any scale. Founded in 2024, headquartered in Remote, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
84/100
Starting Price
Custom
Key Differences at a Glance
In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: Chatbot Platform versus RAG Platform. These differences make each platform better suited for specific use cases and organizational requirements.
⚠️ What This Comparison Covers
We'll analyze features, pricing, performance benchmarks, security compliance, integration capabilities, and real-world use cases to help you determine which platform best fits your organization's needs. All data is independently verified from official documentation and third-party review platforms.
Detailed Feature Comparison
Botpress
Supavec
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Supported Formats: PDF, Word (DOC/DOCX), HTML, TXT, Markdown files via Studio UI and Files API
Website Crawling: Firecrawl integration for HTML-to-Markdown conversion with automatic sitemap detection
Real-Time Search: "Search The Web" feature using Bing API for queries when sitemaps unavailable
Cloud Integrations: Google Drive (OAuth sync with file upload/download triggers), Notion (database queries, page management)
Missing Integrations: No native Dropbox or Salesforce document ingestion
YouTube Limitation: No transcript ingestion support - requires manual transcription and text upload (Apify workaround exists but manual)
Automatic Retraining: Website sources sync regularly, file uploads managed dynamically through Files API
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.
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
Native Channels: WhatsApp (Meta Business API), Slack (OAuth + Bot Framework), Microsoft Teams (Azure portal), Telegram (BotFather), Messenger, Instagram
SMS Support: Twilio and Vonage integrations for text messaging
Web Widget: JavaScript widget (recommended), DOM element mounting, full React component library for SPAs
Mobile Integration: React Native SDK (BpWidget, BpIncomingMessagesListener) for iOS/Android cross-platform support
Webhook Support: Unique webhook URL per bot with optional x-bp-secret header authentication and CORS configuration
Automation Platforms: Zapier integration (partially in beta - some features require manual activation)
Conversational AI: Multi-turn dialogue with context retention across conversation sessions
Multi-Lingual: 100+ languages supported via Translator Agent with automatic translation
Knowledge Base Integration: RAG-powered answers grounded in uploaded documents and websites
Policy Agent: Customizable guardrails filtering outputs against defined policies for brand safety
Knowledge Agent: Structured retrieval before generation to reduce hallucinations
HITL Agent: Human-in-the-loop takeover when bot cannot answer (requires Team plan $495/month)
Personality Agent: Rewrites all bot messages to match defined persona (friendly, professional, casual, custom)
Autonomous Nodes: LLM decides which actions to execute based on conversation context
Performance Claims: "Zero hallucinations in 100,000 conversations" for health coaching client, 65% ticket deflection (no RAGAS scores or latency benchmarks published)
Stateless RAG Architecture: Pure retrieval and generation without built-in conversation state—developers implement multi-turn context and session management in application layer
Model-Agnostic Generation: Defaults to GPT-3.5 but supports GPT-4, self-hosted LLMs (Llama, Mistral), and any OpenAI-compatible models—no vendor lock-in for generation
Postgres Vector Search: Fast approximate nearest neighbor search using pgvector extension with cosine similarity—handles millions of chunks efficiently at enterprise scale
Metadata Filtering: Custom metadata tagging and filtering capabilities enabling organized knowledge management and multi-tenant architectures
Real-Time Re-Indexing: Almost instant document re-embedding when updating or overwriting knowledge sources—no lengthy reprocessing delays
REST API Foundation: Straightforward endpoints for file uploads, text uploads, and search with plain-JSON responses—easy integration from any programming language
Supabase Integration: Built on Supabase infrastructure leveraging PostgreSQL, Row-Level Security (RLS), and battle-tested backend for familiar deployment
LIMITATION - No Built-In Chat UI: API-only platform requiring developers to build custom chat interfaces—not a turnkey chatbot solution with widgets
LIMITATION - No Lead Capture: No built-in lead generation, email collection, or CRM integration capabilities—must be implemented at application layer
LIMITATION - No Human Handoff: No escalation workflows, live agent transfer, or fallback mechanisms—conversational features are developer responsibility
LIMITATION - No Multi-Channel Integrations: No native Slack, Teams, WhatsApp, or messaging platform connectors—developers build integration layer
LIMITATION - No Session Management: Stateless API design without conversation history tracking or multi-turn context retention—application must manage state
LIMITATION - No Advanced RAG: Missing hybrid search, reranking, knowledge graphs, multi-query retrieval, query expansion found in enterprise platforms
LIMITATION - No Observability Dashboard: No analytics, conversation metrics, or performance monitoring UI—must integrate external logging tools
Custom AI Agents: Build autonomous agents powered by GPT-4 and Claude that can perform tasks independently and make real-time decisions based on business knowledge
Decision-Support Capabilities: AI agents analyze proprietary data to provide insights, recommendations, and actionable responses specific to your business domain
Multi-Agent Systems: Deploy multiple specialized AI agents that can collaborate and optimize workflows in areas like customer support, sales, and internal knowledge management
Memory & Context Management: Agents maintain conversation history and persistent context for coherent multi-turn interactions
View Agent Documentation
Tool Integration: Agents can trigger actions, integrate with external APIs via webhooks, and connect to 5,000+ apps through Zapier for automated workflows
Hyper-Accurate Responses: Leverages advanced RAG technology and retrieval mechanisms to deliver context-aware, citation-backed responses grounded in your knowledge base
Continuous Learning: Agents improve over time through automatic re-indexing of knowledge sources and integration of new data without manual retraining
Customization & Branding
Webchat Customization: Full CSS override via external stylesheet URL, custom colors/fonts/button styles/chat bubbles
Branding Control: Custom bot name and avatar, proactive greeting messages via JavaScript, configurable placement and sizing
White-Labeling: Remove "Powered by Botpress" watermark (requires Plus plan $89/month minimum)
Personality Configuration: Personality Agent defines bot persona with variable expressions for dynamic context
Persona Disable: Can be disabled at node level for specific interactions requiring different tone
Backend Branding: Admin dashboard remains Botpress-branded (no full white-label backend)
Multi-Tenant Limitation: No agency dashboard for managing multiple client bots under one interface
Real-Time Updates: Knowledge sources update via Files API without bot republishing for Table-based sources
Versioning Gap: No native versioning system - file replacement is manual with external version control required for rollback
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.
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.
No Python SDK: Significant limitation for data science teams - other languages must use direct REST API access
Authentication: Three token types - Personal Access Token (PAT) for full access, Bot Access Key (BAK) for runtime, Integration Access Key (IAK) for integration-specific actions
Rate Limits: Exist but specifics not publicly documented - Studio limits lower than production bot limits (acknowledged by staff)
Documentation: Well-organized at botpress.com/docs with API references, video tutorials, "Ask AI" feature
Training Resources: Botpress Academy offers free courses
Client Results: Zero hallucinations in 100,000 conversations (health coaching client), 65% ticket deflection
Benchmark Gap: No RAGAS scores, latency measurements, or third-party validation published
Learnings System: Dynamically provides relevant examples at prompt-time to improve responses
Vector Storage: Purpose-built vector database with plan-based scaling (100MB to custom Enterprise)
Standard RAG architecture: Document chunking with vector embeddings stored in Postgres pgvector extension for semantic search
Embedding generation: Automatic embedding creation during document upload using OpenAI embedding models or custom embedding endpoints
Vector search: Postgres vector search with cosine similarity for retrieval, handling millions of chunks efficiently
Re-indexing speed: Almost instant document re-embedding when updating or overwriting knowledge sources
Metadata support: Custom metadata tagging and filtering capabilities for organized knowledge management
Note: No advanced RAG features: No hybrid search (semantic + keyword), no reranking, no multi-query retrieval, no query expansion
Note: No hallucination detection: No built-in citation validation, factual consistency scoring, or confidence thresholds - developers must implement manually
Note: No retrieval parameter controls: Chunking strategy, similarity thresholds, and top-k configuration require code-level changes
Core architecture: GPT-4 combined with Retrieval-Augmented Generation (RAG) technology, outperforming OpenAI in RAG benchmarks
RAG Performance
Anti-hallucination technology: Advanced mechanisms reduce hallucinations and ensure responses are grounded in provided content
Benchmark Details
Automatic citations: Each response includes clickable citations pointing to original source documents for transparency and verification
Optimized pipeline: Efficient vector search, smart chunking, and caching for sub-second reply times
Scalability: Maintains speed and accuracy for massive knowledge bases with tens of millions of words
Context-aware conversations: Multi-turn conversations with persistent history and comprehensive conversation management
Source verification: Always cites sources so users can verify facts on the spot
Omnichannel Deployment
Messaging Platforms: WhatsApp (Meta Business API), Slack (OAuth + Bot Framework), Microsoft Teams (Azure portal registration)
Social Media: Telegram (BotFather setup - easy), Messenger, Instagram (Meta integration - medium complexity)
SMS Support: Twilio and Vonage integrations for text messaging channels
Web Deployment: JavaScript widget (recommended), DOM element mounting, React component library for SPAs
Mobile Apps: React Native SDK (BpWidget, BpIncomingMessagesListener) for iOS/Android cross-platform integration
Webhook Architecture: Unique webhook URL per bot with optional x-bp-secret header authentication
CORS Configuration: Customizable for web embedding and API access
Deployment Complexity: Ranges from easy (Telegram) to complex (Microsoft Teams Azure setup, WhatsApp Meta Business)
Hub Marketplace: 100+ integrations for extended channel and platform support
N/A
N/A
Visual Bot Building
Node-Based Canvas: Drag-and-drop conversation flow design with visual connections between nodes
Action Cards: Pre-built components for Text responses, Capture Information (forms), Execute Code (TypeScript), AI Tasks, Knowledge Base queries
Integration Actions: Direct connections to CRM (Salesforce, HubSpot), support (Zendesk), data sources
Autonomous Nodes: LLM-driven decision making for dynamic conversation paths without manual flow definition
Code Extensibility: Execute Code cards allow full TypeScript programming within visual flows
Knowledge Base Management: Visual drag-and-drop file upload, URL ingestion, text input, Tables for structured data
Template Library: ~8 official pre-built bots (Recipe, Recruitment, Support, Cinema, AI Dungeon Master) + community contributions
Real-Time Testing: Test conversations directly in Studio before deployment
Version Control: No native system - requires external Git integration and manual management
N/A
N/A
R A G-as-a- Service Assessment
Platform Type: CONVERSATIONAL AI PLATFORM WITH RAG (not pure RAG service)
Core Architecture: Full bot builder with integrated RAG capabilities (semantic chunking, vector storage, retrieval)
Service Model: Cloud SaaS with visual development environment and omnichannel deployment
RAG Implementation: Standard pipeline with semantic chunking, Policy Agent guardrails, Knowledge Agent retrieval
LLM Integration: Native OpenAI support only - alternatives require custom workarounds
Citation Support: Knowledge Agent provides source references but specificity level not documented
Enterprise Readiness: SOC 2 in progress (not certified), no EU data residency, not HIPAA compliant
RAG Focus: RAG is one feature within comprehensive conversational AI platform, not standalone RAG API
Platform Type: TRUE RAG-AS-A-SERVICE API - Lightweight MIT-licensed open-source RAG backend built on Supabase with self-hosting capability and minimal API surface
Core Mission: Provide transparent, open-source alternative to proprietary RAG services (Carbon.ai shutdown response) with full cost control and no vendor lock-in
Target Market: Developers building custom RAG applications on budget, startups minimizing costs with self-hosting, organizations requiring data sovereignty with Supabase infrastructure
RAG Implementation: Standard RAG architecture with document chunking, OpenAI embeddings, Postgres pgvector semantic search—focused on simplicity over advanced techniques
API-First Design: Pure REST API for retrieval and generation without GUI, widgets, or conversational features—intentionally minimal abstraction for developer control
Self-Hosting Advantage: MIT license enables complete on-premises deployment keeping all data on your servers—ideal for GDPR, HIPAA, data residency compliance
Managed Service Option: Cloud-hosted plans (Free: 100 calls/month, Basic: $190/year for 750 calls/month, Enterprise: $1,490/year for 5K calls/month) eliminate infrastructure management
Pricing Model: Free self-hosting (MIT license) or extremely affordable hosted plans—40-90% cheaper than commercial RAG platforms with no per-document charges or user seat fees
Data Sources: File uploads (PDF, Markdown, TXT) via REST API or raw text ingestion—NO pre-built Google Drive, Notion, or cloud storage connectors (manual scripting required)
Model Flexibility: Model-agnostic with GPT-3.5 default, GPT-4, or self-hosted LLM support—users connect own OpenAI API keys without Supavec markup on AI costs
Security Foundation: Supabase Row-Level Security (RLS) for multi-tenant data isolation, HTTPS encryption, AES-256 at-rest encryption—self-hosting enables GDPR/HIPAA compliance
Support Model: Community GitHub/Discord support for free tier, email support for paid plans—no dedicated CSMs, SLAs, or enterprise account management
Open-Source Ecosystem: Transparent code on GitHub welcoming PRs, forks, and community contributions—no proprietary components or vendor lock-in
LIMITATION - Developer-Only Platform: Requires coding skills for setup, integration, and maintenance—non-technical teams cannot use without developer support
LIMITATION - Basic RAG Features: Standard retrieval without hybrid search, reranking, knowledge graphs, multi-query fusion, or hallucination detection—advanced features require custom development
LIMITATION - No Turnkey Features: No GUI dashboard, conversation management, lead capture, analytics, or multi-channel integrations—pure RAG API requiring application layer development
Comparison Validity: Architectural comparison to full-featured chatbot platforms like CustomGPT.ai requires context—Supavec is lightweight RAG backend API vs complete no-code chatbot builder
Use Case Fit: Perfect for developers wanting lightweight RAG backend without heavy frameworks, startups minimizing costs with Supabase self-hosting, teams building custom chatbots needing simple REST API for retrieval without paying for unused dashboard features
Core Architecture: Serverless RAG infrastructure with automatic embedding generation, vector search optimization, and LLM orchestration fully managed behind API endpoints
API-First Design: Comprehensive REST API with well-documented endpoints for creating agents, managing projects, ingesting data (1,400+ formats), and querying chat
API Documentation
Developer Experience: Open-source Python SDK (customgpt-client), Postman collections, OpenAI API endpoint compatibility, and extensive cookbooks for rapid integration
No-Code Alternative: Wizard-style web dashboard enables non-developers to upload content, brand widgets, and deploy chatbots without touching code
Hybrid Target Market: Serves both developer teams wanting robust APIs AND business users seeking no-code RAG deployment - unique positioning vs pure API platforms (Cohere) or pure no-code tools (Jotform)
RAG Technology Leadership: Industry-leading answer accuracy (median 5/5 benchmarked), 1,400+ file format support with auto-transcription, proprietary anti-hallucination mechanisms, and citation-backed responses
Benchmark Details
Deployment Flexibility: Cloud-hosted SaaS with auto-scaling, API integrations, embedded chat widgets, ChatGPT Plugin support, and hosted MCP Server for Claude/Cursor/ChatGPT
Enterprise Readiness: SOC 2 Type II + GDPR compliance, full white-labeling, domain allowlisting, RBAC with 2FA/SSO, and flat-rate pricing without per-query charges
Use Case Fit: Ideal for organizations needing both rapid no-code deployment AND robust API capabilities, teams handling diverse content types (1,400+ formats, multimedia transcription), and businesses requiring production-ready RAG without building ML infrastructure from scratch
Competitive Positioning: Bridges the gap between developer-first platforms (Cohere, Deepset) requiring heavy coding and no-code chatbot builders (Jotform, Kommunicate) lacking API depth - offers best of both worlds
Competitive Positioning
Primary Advantage: Visual bot building with code extensibility - accessible to non-developers, powerful for developers
Scale Validation: 750,000+ active bots and 1 billion+ messages processed prove production reliability at massive scale
Omnichannel Strength: Comprehensive native support for WhatsApp, Slack, Teams, Telegram, Messenger, SMS, web, mobile
Community Power: 31,000+ Discord members provide peer support, troubleshooting, best practices, feature validation
Primary Challenge: SOC 2 not certified, no EU data residency - critical gaps for enterprise buyers with compliance needs
Security Gap: Not HIPAA compliant, no ISO 27001 - blocks regulated industry adoption (healthcare, finance)
Cost Trade-Off: Free tier available but AI Spend unpredictability + feature paywalls (RBAC at $495/month) add complexity
Market Position: Conversational AI platform competing with Dialogflow, Rasa, Microsoft Bot Framework vs. pure RAG services
Use Case Fit: Ideal for teams needing visual bot building + multi-channel deployment vs. pure RAG API integrations
Platform vs. API: Full development environment with Studio, not lightweight RAG API - different target audience than CustomGPT
Market position: MIT-licensed open-source RAG API built on Supabase, offering lightweight alternative to Carbon.ai with self-hosting capability and minimal API surface
Target customers: Developers building custom RAG applications on budget, startups wanting to avoid RAG platform costs, and organizations requiring self-hosted solutions with Supabase infrastructure for data sovereignty
Key competitors: Carbon.ai, LangChain, SimplyRetrieve, and hosted RAG APIs like CustomGPT/Pinecone Assistant
Competitive advantages: MIT open-source license with no vendor lock-in, Supabase foundation for familiar infrastructure, model-agnostic with easy LLM swapping (GPT-3.5, GPT-4, self-hosted), REST API simplicity with straightforward endpoints, privacy-focused with self-hosting option keeping data on your servers, and minimal abstraction enabling deep customization
Pricing advantage: Free (MIT license) for self-hosting; hosted plans extremely affordable ($190/year Basic for 750 calls/month, $1,490/year Enterprise for 5K calls/month); best value for low-volume applications or teams with Supabase expertise wanting to avoid expensive RAG platforms; 40-90% cheaper than commercial alternatives
Use case fit: Perfect for developers wanting lightweight RAG backend without heavy frameworks, startups minimizing costs with self-hosting on existing Supabase infrastructure, and teams building custom chatbot front-ends needing simple REST API for retrieval without paying for unused dashboard features
Market position: Leading all-in-one RAG platform balancing enterprise-grade accuracy with developer-friendly APIs and no-code usability for rapid deployment
Target customers: Mid-market to enterprise organizations needing production-ready AI assistants, development teams wanting robust APIs without building RAG infrastructure, and businesses requiring 1,400+ file format support with auto-transcription (YouTube, podcasts)
Key competitors: OpenAI Assistants API, Botsonic, Chatbase.co, Azure AI, and custom RAG implementations using LangChain
Competitive advantages: Industry-leading answer accuracy (median 5/5 benchmarked), 1,400+ file format support with auto-transcription, SOC 2 Type II + GDPR compliance, full white-labeling included, OpenAI API endpoint compatibility, hosted MCP Server support (Claude, Cursor, ChatGPT), generous data limits (60M words Standard, 300M Premium), and flat monthly pricing without per-query charges
Pricing advantage: Transparent flat-rate pricing at $99/month (Standard) and $449/month (Premium) with generous included limits; no hidden costs for API access, branding removal, or basic features; best value for teams needing both no-code dashboard and developer APIs in one platform
Use case fit: Ideal for businesses needing both rapid no-code deployment and robust API capabilities, organizations handling diverse content types (1,400+ formats, multimedia transcription), teams requiring white-label chatbots with source citations for customer-facing or internal knowledge projects, and companies wanting all-in-one RAG without managing ML infrastructure
A I Models
Native OpenAI Support: GPT-4o, GPT-4o mini, GPT-4 Turbo with in-Studio presets ("Best Model" and "Fast Model" for quick selection)
Claude Models: Claude 4 Sonnet, Claude 3.5 Sonnet, Claude 3.7 Sonnet, Claude 4.5 Sonnet accessible via custom integrations or Execute Code cards
Google Gemini: Gemini Pro, Gemini 2.5 Flash available through external API calls in custom integrations
Open Source Options: LLaMA, DeepSeek accessible via Execute Code cards with external API integration
Model Access within Days: Platform provides access to latest LLMs within days of release for every chatbot built on Botpress
No Automatic Routing: Deliberately avoided for "concerns about unpredictability and latency" - users manually select models per task
LLMz Engine: Proprietary inference layer with claimed improvements - better tool calling, token efficiency, TypeScript type definitions, V8 isolate execution
AI Spend Pricing: Charged at-cost with no Botpress markup on OpenAI tokens; option to use Botpress-managed credits or BYOK (bring your own key)
No Fine-Tuning: RAG recommended as primary approach, supplemented by "learnings" system providing relevant examples at prompt-time
Model-agnostic architecture: Defaults to GPT-3.5 Turbo for cost-effectiveness, with full support for GPT-4, GPT-4-turbo, and any OpenAI-compatible models
Self-hosted model support: Bring your own LLM - compatible with self-hosted models like Llama, Mistral, or custom fine-tuned models via API endpoints
No model lock-in: Switch between models by changing configuration or prompt path in code without platform restrictions
No markup on AI costs: Users connect their own OpenAI API keys or self-hosted endpoints, paying providers directly without Supavec markup
Note: No built-in model routing: No automatic model selection or load balancing - developers must implement routing logic manually
Note: No prompt optimization layer: Plain RAG implementation without advanced prompt engineering or anti-hallucination guardrails
Quality dependency: Output quality rests entirely on chosen LLM and developer's prompt engineering skills
Primary models: GPT-5.1 and 4 series from OpenAI, and Anthropic's Claude 4.5 (opus and sonnet) for enterprise needs
Automatic model selection: Balances cost and performance by automatically selecting the appropriate model for each request
Model Selection Details
Proprietary optimizations: Custom prompt engineering and retrieval enhancements for high-quality, citation-backed answers
Managed infrastructure: All model management handled behind the scenes - no API keys or fine-tuning required from users
Anti-hallucination technology: Advanced mechanisms ensure chatbot only answers based on provided content, improving trust and factual accuracy
Use Cases
Customer Support: Most popular use case with 98% of chats resolved without human intervention (Ruby Labs: 4 million support chats monthly)
Sales Automation: Majority of deployed bots part of sales process - appointment scheduling, lead nurturing, product suggestions, competitive comparisons, automated follow-ups
Sales Impact: Businesses report average 67% sales increase using chatbots, projected $112 billion in retail sales for 2024
Enterprise Internal Use: HR chatbots for vacation requests, IT chatbots for employee tech troubleshooting, repetitive high-volume task automation
Lead Generation: AI lead generation qualifies leads through conversational engagement, needs assessment, information gathering, automated follow-up
Cost Savings: One bank saved €530,000 by deploying chatbot, demonstrating measurable enterprise ROI
Multi-Channel Engagement: WhatsApp Business API, Slack, Microsoft Teams, Telegram, Messenger, Instagram, SMS (Twilio/Vonage) for comprehensive reach
Scale Validation: 750,000+ active bots, 1 billion+ messages processed provide real-world production reliability proof
Custom chatbot backends: Ideal for developers building custom chat interfaces needing simple RAG API without heavy platform overhead
Self-hosted knowledge retrieval: Perfect for organizations requiring data sovereignty with Supabase infrastructure for compliance (GDPR, HIPAA when self-hosted)
Budget-conscious RAG applications: Startups and small teams minimizing costs with MIT open-source license and affordable hosted plans ($190-$1,490/year)
Supabase-native projects: Teams already using Supabase can integrate Supavec seamlessly without additional infrastructure complexity
Developer-first RAG: Code-first teams wanting full control over RAG implementation, eschewing GUI dashboards for API-driven workflows
Not ideal for: Non-technical users requiring no-code interfaces, enterprises needing advanced RAG features (hybrid search, reranking), or teams requiring built-in analytics/monitoring
Not ideal for: Production applications requiring hallucination detection, citation validation, or confidence scoring without custom development
Customer support automation: AI assistants handling common queries, reducing support ticket volume, providing 24/7 instant responses with source citations
Internal knowledge management: Employee self-service for HR policies, technical documentation, onboarding materials, company procedures across 1,400+ file formats
Sales enablement: Product information chatbots, lead qualification, customer education with white-labeled widgets on websites and apps
Documentation assistance: Technical docs, help centers, FAQs with automatic website crawling and sitemap indexing
Educational platforms: Course materials, research assistance, student support with multimedia content (YouTube transcriptions, podcasts)
Healthcare information: Patient education, medical knowledge bases (SOC 2 Type II compliant for sensitive data)
Data Retention: Automatic deletion of personal log data, API endpoints for GDPR "right to be forgotten" compliance
Training Privacy: Conversation data NOT used to train Botpress or third-party models
Self-hosting advantage: MIT license enables complete data sovereignty - all data stays on your servers for strict compliance requirements
[Privacy note]
Supabase security foundation: Row-level security (RLS) fences off each team's data when using hosted Supavec on Supabase infrastructure
No model training: Your documents never used for LLM training - data remains yours with zero retention by OpenAI or other providers
GDPR/HIPAA ready: Self-hosting enables GDPR and HIPAA compliance when deployed on compliant infrastructure - enterprises can go dedicated or on-premises
Encryption: Standard HTTPS encryption for API calls; at-rest encryption depends on hosting infrastructure (Supabase provides AES-256)
Note: No SOC 2 certification: Open-source project lacks formal SOC 2 Type II, ISO 27001, or other enterprise compliance certifications for hosted plans
Note: No built-in access controls: Authentication, authorization, and RBAC must be implemented by developers in their application layer
Note: Limited hosted security features: Hosted plans lack SSO/SAML, IP whitelisting, or advanced security controls without custom configuration
Encryption: SSL/TLS for data in transit, 256-bit AES encryption for data at rest
SOC 2 Type II certification: Industry-leading security standards with regular third-party audits
Security Certifications
GDPR compliance: Full compliance with European data protection regulations, ensuring data privacy and user rights
Access controls: Role-based access control (RBAC), two-factor authentication (2FA), SSO integration for enterprise security
Data isolation: Customer data stays isolated and private - platform never trains on user data
Domain allowlisting: Ensures chatbot appears only on approved sites for security and brand protection
Secure deployments: ChatGPT Plugin support for private use cases with controlled access
Pricing & Plans
Pay-as-you-go (Free): $0/month + AI Spend, 500 messages, 100MB vector storage, 1 bot, 1 collaborator, $5 AI credit included
Plus Plan: $89/month + AI Spend, 5,000 messages, 1GB vector storage, white-label, HITL, live chat support
Team Plan: $495/month + AI Spend, 50,000 messages, 2GB vector storage, RBAC, collaboration, 3 bots, custom analytics
Enterprise Contracts: May require multi-year commitments (3-year contracts mentioned in reviews)
Enterprise SLA: 99.8% uptime guarantee with service credits (5-25% depending on severity), maximum monthly credit 50% of charges
Open-source (Free): MIT-licensed for self-hosting - pay only your infrastructure costs (Supabase, server, storage) with unlimited API calls and no vendor fees
Hosted Free tier: 100 API calls per month for development and testing
[Pricing]
Basic Plan: $190/year ($15.83/month equivalent) - 750 API calls per month, hosted infrastructure, automatic backups, email support
Enterprise Plan: $1,490/year ($124.17/month equivalent) - 5,000 API calls per month, priority support, SLA guarantees, dedicated resources
No per-document charges: Storage not metered separately - only query volume counts toward plan limits
No user seat fees: Pricing based purely on API call volume, not team size or number of developers
Need more calls? Negotiate custom limits with hosted provider or self-host to eliminate caps entirely
Value proposition: 40-90% cheaper than commercial RAG platforms - Basic plan costs less than 1 month of competing platforms while providing annual service
Standard Plan: $99/month or $89/month annual - 10 custom chatbots, 5,000 items per chatbot, 60 million words per bot, basic helpdesk support, standard security
View Pricing
Premium Plan: $499/month or $449/month annual - 100 custom chatbots, 20,000 items per chatbot, 300 million words per bot, advanced support, enhanced security, additional customization
Enterprise Plan: Custom pricing - Comprehensive AI solutions, highest security and compliance, dedicated account managers, custom SSO, token authentication, priority support with faster SLAs
Enterprise Solutions
7-Day Free Trial: Full access to Standard features without charges - available to all users
Annual billing discount: Save 10% by paying upfront annually ($89/mo Standard, $449/mo Premium)
Flat monthly rates: No per-query charges, no hidden costs for API access or white-labeling (included in all plans)
Managed infrastructure: Auto-scaling cloud infrastructure included - no additional hosting or scaling fees
Support & Documentation
Free Plan Support: Community only - Discord (31,000+ members), documentation, forums - no direct support
Plus Plan Support: Live chat with Botpress engineers ($89/month) for direct technical assistance
Team Plan Support: Advanced support + solution engineering ($495/month) for complex implementations
Enterprise Support: Named support manager, SLA-backed response times (2 hours to 2 business days), ~$2,000+/month
Discord Community: 31,000+ highly active members with daily discussions, feature requests, troubleshooting - praised as "best Discord experience"
Documentation: Comprehensive docs at botpress.com/docs with API references, video tutorials, "Ask AI" feature for guided help
Botpress Academy: Free training courses covering bot development, best practices, advanced features
Response Time SLAs: 2 business days (standard Level 1) to 2 hours (premium Level 1) for Enterprise customers
Service Credits: 99.8% uptime SLA with credits for downtime, includes OpenAI unavailability (notable external dependency caveat)
Support Limitation: Non-Enterprise users lack formal ticketing system, may experience wait times for complex issues
Documentation: Lean API reference docs focusing on endpoint usage with JavaScript code snippets - mostly technical rather than tutorial-heavy
[Docs]
Community support: GitHub Discussions and Discord for free tier and self-hosted users - community-driven help and troubleshooting
Email support: Paid plan users (Basic/Enterprise) get email support with priority levels based on tier
No dedicated CSM: No Customer Success Manager or account management even on Enterprise tier - support ticket-based
GitHub repository: Open-source code welcomes PRs, issues, and community contributions - active maintainer responses
Postman collection: API documentation includes Postman collection for quick testing and integration
Code samples: Community-contributed examples and integrations appearing in GitHub issues and Discord, but not extensive official library
Learning curve: Requires developer skills - no video tutorials, webinars, or certification programs like commercial platforms
Documentation hub: Rich docs, tutorials, cookbooks, FAQs, API references for rapid onboarding
Developer Docs
Email and in-app support: Quick support via email and in-app chat for all users
Premium support: Premium and Enterprise plans include dedicated account managers and faster SLAs
Code samples: Cookbooks, step-by-step guides, and examples for every skill level
API Documentation
Active community: User community plus 5,000+ app integrations through Zapier ecosystem
Regular updates: Platform stays current with ongoing GPT and retrieval improvements automatically
Additional Considerations
High learning curve: Platform highly flexible but non-technical users struggle with advanced flow builder and developer-oriented features
Developer dependency: No quick copy-and-paste solution for real enterprise - company needs long-term employees ready to see it through with recommended 1-2 developers and 1-2 business-side employees per project
Performance under load: Live users report latency and webhook timeout issues under spiky high-concurrency loads - high-traffic teams should stress-test with projected peak traffic
Self-hosting complexity: For enterprise deployments with large numbers of bots or conversations self-hosting might be required shifting maintenance and scaling challenges to your team
Technical requirements: Configuring Docker, Kubernetes, databases, and certificates can become roadblock - requires skills in JavaScript, API integration, NLP, state management
DevOps investment needed: Teams should be prepared for additional DevOps investment for autoscaling, database sharding, and backup strategies
Unpredictable AI usage costs: Every message, retrieval, or workflow call consumes tokens making monthly bills swing dramatically depending on traffic and complexity
Hidden expenses: Third-party services like WhatsApp, SMS, voice integrations billed separately - advanced use cases often require engineering hours, enterprise deployments may require onboarding packages, compliance audits, or custom module builds costing thousands
Scaling costs: Growing from 5,000 to 20,000 MAUs means moving from $495/month to much higher custom enterprise price - multiple bots, custom integrations, or premium add-ons can push monthly spend well past initial plan quote
Resource-heavy features: Botpress LLM features can be resource-heavy requiring wise CPU/memory allocation planning
Commercial license threshold: Planning more than 150K interactions per month requires commercial license
Ongoing maintenance: Deployment is just start - bots must be continuously monitored, tested, and iterated to stay effective and aligned with evolving business goals
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.
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.
Core Chatbot Features
Advanced AI capabilities: Extremely advanced AI with multiple sophisticated AI agents - automatic translation, conversation summarization, Vision Agent for image understanding
LLMz custom inference engine: Core of every Botpress agent with proprietary engine for enhanced performance
Conversational memory: Rich conversational memory maintaining context across long interactions, understanding complex multi-turn queries, and generating human-like responses
User memory across sessions: Agent remembers conversation history of specific users across different times - recalls user preferences, where they left off, and preferred tone of voice
Visual flow builder: Drag-and-drop interface for designing complex conversational flows without coding
Built-in AI features: Intent recognition, entity extraction, knowledge base integration, and AI agents
Custom data training: Train chatbot on custom data like website and documents
Multi-channel deployment: Create and launch chatbots on many channels including website, Facebook, WhatsApp, Slack, Instagram and more platforms
API integrations: Integrates with APIs, CRMs, databases, and other business applications
Automatic translation: Over 100 languages for global reach
AI Swarms/Teams (2025): Platform transformed into mature "AI workforce deployment and management center" with AI team collaboration capabilities
Live Database Connectors: Breakthrough feature allowing direct secure connection to SQL or NoSQL database in addition to traditional API connections
Open-source flexibility: Users have access to application source code and can contribute to development - skilled developers can push envelope to tailor to unique needs
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.
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.
Knowledge Bases: Upload in variety of formats ranging from website or document to custom text file or Table
Knowledge Base scoping: Scope which Knowledge Bases Autonomous Node searches by organizing documents into folders limiting availability to certain workflows
Search field configuration: Configure search fields such as name, description, power, price to refine bot responses
Dynamic management: Programmatically manage Knowledge Base files with Botpress API to dynamically add, update, or remove content in real time keeping AI agent knowledge current
Behavior customization: Define specific behaviors in instructions to avoid unintended outputs - specify prices are final and include all discounts to prevent bot from fabricating discounts
Custom responses: Program custom response by adding Transition Card in Autonomous Node and handle transition however wanted with custom error messages
Bot templates: Pre-configured projects containing predefined conversational flows, Knowledge Bases, and responses serving as starting point - easily customized and extended to meet specific requirements with full developer control
Visual customization: Give bot name, store avatar URL for custom icon, provide general description, formulate placeholder text displayed before user enters first text
ChatGPT consultation: Customize bot behavior deciding when to consult ChatGPT based on knowledge base responses
Highly customizable workflows: Unlimited variables and open-source flexibility for advanced customization
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.
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.
Limitations & Considerations
Steep Learning Curve: Platform highly flexible but non-technical users struggle with advanced flow builder and developer-oriented features
Developer Dependency: Requires developer involvement making it less suitable for small businesses needing quick setup
Bug Disruptions: Various bugs may disrupt workflows and cause functionality problems requiring troubleshooting
Missing Features: White-labeling, global compliance, seamless live support require heavy effort or unavailable, slowing adoption
Data Visibility Gap: Cannot see user variables (name, email, custom fields) in chatbot conversations - limits analytics capabilities
Cost for SMBs: Enterprise-level security, compliance, dedicated support cost prohibitive for smaller teams ($495-$2,000+/month)
Resource Requirements: Self-hosted deployment requires IT resources for deployment and ongoing management
Complex Setup: Publishing on Facebook/Instagram technically complex, live chat only available on higher-priced plans
Limited Analytics: Standard plans offer limited analytical capabilities - advanced analytics require Team plan ($495/month)
LLM Provider Dependency: Reliance on third-party LLM providers (primarily OpenAI) impacts operational costs, scalability, and control
Complex Issue Handling: Chatbots may struggle with handling complex, nuanced customer issues requiring human judgment
Multi-Instance Challenges: Setting up multiple instances from one installation proven difficult for some enterprise users
Compliance Gaps: SOC 2 incomplete, no HIPAA, no ISO 27001, US-only data residency blocks regulated industries and EU enterprises
No GUI/dashboard: Everything via API or CLI - no business-user interface for content management, analytics, or configuration
Developer-only tool: Requires coding skills for setup, integration, and maintenance - non-technical teams cannot use without developer support
Basic RAG only: Standard retrieval-augmented generation without advanced features like hybrid search, query reranking, multi-query fusion, or query expansion
No observability built-in: No metrics dashboard, conversation analytics, or performance monitoring - must wire up your own logging layer
Manual hallucination handling: No built-in citation validation, confidence scoring, or factual consistency checks - developers must implement safeguards
Limited connectors: No one-click Google Drive, Notion, or cloud storage integrations - must script data fetching and API uploads manually
No conversation management: Stateless API calls without chat history, multi-turn context, or session management - build conversation layer yourself
Infrastructure knowledge required: Self-hosting requires Supabase, Postgres, and vector database expertise - not plug-and-play for non-DevOps teams
Minimal abstraction: Intentionally low-level API design provides control but requires more integration work than higher-level RAG platforms
Managed service approach: Less control over underlying RAG pipeline configuration compared to build-your-own solutions like LangChain
Vendor lock-in: Proprietary platform - migration to alternative RAG solutions requires rebuilding knowledge bases
Model selection: Limited to OpenAI (GPT-5.1 and 4 series) and Anthropic (Claude, opus and sonnet 4.5) - no support for other LLM providers (Cohere, AI21, open-source models)
Pricing at scale: Flat-rate pricing may become expensive for very high-volume use cases (millions of queries/month) compared to pay-per-use models
Customization limits: While highly configurable, some advanced RAG techniques (custom reranking, hybrid search strategies) may not be exposed
Language support: Supports 90+ languages but performance may vary for less common languages or specialized domains
Real-time data: Knowledge bases require re-indexing for updates - not ideal for real-time data requirements (stock prices, live inventory)
Enterprise features: Some advanced features (custom SSO, token authentication) only available on Enterprise plan with custom pricing
After analyzing features, pricing, performance, and user feedback, both Botpress and Supavec are capable platforms that serve different market segments and use cases effectively.
When to Choose Botpress
You value visual drag-and-drop builder with extensive code extensibility via execute code cards
Massive scale validation: 750,000+ active bots, 1 billion+ messages processed
Comprehensive omnichannel support: WhatsApp, Slack, Teams, Telegram, Messenger, SMS, web
Best For: Visual drag-and-drop builder with extensive code extensibility via Execute Code cards
When to Choose Supavec
You value 100% open source with no vendor lock-in
Complete control over data and infrastructure
Strong privacy with Supabase RLS integration
Best For: 100% open source with no vendor lock-in
Migration & Switching Considerations
Switching between Botpress and Supavec requires careful planning. Consider data export capabilities, API compatibility, and integration complexity. Both platforms offer migration support, but expect 2-4 weeks for complete transition including testing and team training.
Pricing Comparison Summary
Botpress starts at custom pricing, while Supavec begins at custom pricing. Total cost of ownership should factor in implementation time, training requirements, API usage fees, and ongoing support. Enterprise deployments typically see annual costs ranging from $10,000 to $500,000+ depending on scale and requirements.
Our Recommendation Process
Start with a free trial - Both platforms offer trial periods to test with your actual data
Define success metrics - Response accuracy, latency, user satisfaction, cost per query
Test with real use cases - Don't rely on generic demos; use your production data
Evaluate total cost - Factor in implementation time, training, and ongoing maintenance
Check vendor stability - Review roadmap transparency, update frequency, and support quality
For most organizations, the decision between Botpress and Supavec comes down to specific requirements rather than overall superiority. Evaluate both platforms with your actual data during trial periods, focusing on accuracy, latency, ease of integration, and total cost of ownership.
📚 Next Steps
Ready to make your decision? We recommend starting with a hands-on evaluation of both platforms using your specific use case and data.
• Review: Check the detailed feature comparison table above
• Test: Sign up for free trials and test with real queries
• Calculate: Estimate your monthly costs based on expected usage
• Decide: Choose the platform that best aligns with your requirements
Last updated: December 11, 2025 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.
The most accurate RAG-as-a-Service API. Deliver production-ready reliable RAG applications faster. Benchmarked #1 in accuracy and hallucinations for fully managed RAG-as-a-Service API.
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.
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