SimplyRetrieve vs SiteGPT

Make an informed decision with our comprehensive comparison. Discover which RAG solution perfectly fits your needs.

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 SimplyRetrieve and SiteGPT 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 SimplyRetrieve and SiteGPT, 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 SimplyRetrieve if: you value completely free and open source
  • Choose SiteGPT if: you value extremely easy setup - minutes to launch

About SimplyRetrieve

SimplyRetrieve Landing Page Screenshot

SimplyRetrieve is lightweight retrieval-centric generative ai platform. SimplyRetrieve is an open-source tool providing a fully localized, lightweight, and user-friendly GUI and API platform for Retrieval-Centric Generation (RCG). It emphasizes privacy and can run on a single GPU while maintaining clear separation between LLM context interpretation and knowledge memorization. Founded in 2019, headquartered in Tokyo, Japan, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
82/100
Starting Price
Custom

About SiteGPT

SiteGPT Landing Page Screenshot

SiteGPT is make ai your expert customer support agent. SiteGPT is an AI chatbot solution that instantly answers visitor questions with a personalized chatbot trained on your website content. It's like having ChatGPT specifically for your products, offering 24/7 automated customer support with seamless integrations into existing support platforms. Founded in 2022, headquartered in Remote, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
86/100
Starting Price
$49/mo

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, SimplyRetrieve starts at a lower price point. The platforms also differ in their primary focus: RAG Platform versus AI Chatbot. 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

logo of simplyretrieve
SimplyRetrieve
logo of sitegpt
SiteGPT
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Data Ingestion & Knowledge Sources
  • Uses a hands-on, file-based flow: drop PDFs, text, DOCX, PPTX, HTML, etc. into a folder and run a script to embed them.
  • A new GUI Knowledge-Base editor lets you add docs on the fly, but there’s no web crawler or auto-refresh yet.
  • Crawls entire sites by URL or sitemap—thousands of pages in one go. Learn how
  • Accepts uploads in CSV, TXT, PDF, DOCX, PPTX, and Markdown (10 MB per file). File upload info
  • Connects to Google Drive, Dropbox, OneDrive, Notion, Confluence, GitBook, and more out of the box. View integrations
  • Scales to big libraries—up to 100 k pages on the Enterprise tier.
  • Retraining is manual for now (click a button), with automated retrain cycles on the roadmap. Retraining details
  • 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 with a local Gradio GUI and Python scripts for queries—no out-of-the-box Slack or site widget.
  • Want other channels? Write a small wrapper that forwards messages to your local chatbot.
  • Ships native connectors for Slack, Google Chat, Facebook Messenger, Crisp, Freshchat, Zendesk Chat, Zoho SalesIQ, and more. See Slack integration
  • Embed on any site with a quick script or iframe—works on web and mobile. Embed instructions
  • Higher tiers add webhook support for event-driven hooks into your own systems.
  • Embeds easily—a lightweight script or iframe drops the chat widget into any website or mobile app.
  • Offers ready-made hooks for Slack, Zendesk, Confluence, YouTube, Sharepoint, 100+ more. 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.
  • Hosted CustomGPT.ai offers hosted MCP Server with support for Claude Web, Claude Desktop, Cursor, ChatGPT, Windsurf, Trae, etc. Read more here.
  • Supports OpenAI API Endpoint compatibility. Read more here.
Core Chatbot Features
  • Runs a retrieval-augmented chatbot on open-source LLMs, streaming tokens live in the Gradio UI.
  • Primarily single-turn Q&A; long-term memory is limited in this release.
  • Includes a “Retrieval Tuning Module” so you can see—and tweak—how answers are built from the data.
  • Strong Q&A for support, with multi-turn history visible in the admin dashboard.
  • Handles 95 + languages to help a global audience. Language support
  • Captures leads automatically during chat sessions.
  • Built-in human handoff lets users escalate to a live agent when needed. Escalation details
  • Tracks sentiment and conversation metrics so you can watch performance in real time.
  • 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
  • Default Gradio interface is pretty plain, with minimal theming.
  • For a branded UI you’ll tweak source code or build your own front end.
  • No-code dashboard to swap logos, colors, and welcome text in seconds. Customize appearance
  • White-label add-on removes SiteGPT branding for a seamless look. White-label option
  • Choose preset Personas to set tone and voice for each bot.
  • 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
  • Defaults to WizardVicuna-13B, but you can swap in any Hugging Face model if you have the GPUs.
  • Full control over model choice, though smaller open models won’t match GPT-4 for depth.
  • Pick GPT-4o-mini for speed or full GPT-4o for deeper answers. Model options
  • Select the mode per chatbot, balancing response time against depth as you like.
  • Taps into top models—OpenAI’s GPT-5.1 series, GPT-4 series, and even Anthropic’s Claude for enterprise needs (4.5 opus and sonnet, etc ).
  • 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)
  • Interaction happens via Python scripts—there’s no formal REST API or SDK.
  • Integrations usually call those scripts as subprocesses or add your own wrapper.
  • REST API for bot management, content uploads, and fetching answers. API getting started
  • Manage Quick Prompts and Personas via API—no multi-language SDK yet, but REST makes it straightforward.
  • 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.
Performance & Accuracy
  • Open-source models run slower than managed clouds—expect a few to 10 + seconds per reply on a single GPU.
  • Accuracy is fine when the right doc is found, but smaller models can struggle on complex, multi-hop queries.
  • Retrieval-augmented generation keeps answers factual and on-topic.
  • Two modes (fast vs. accurate) let you choose speed or depth. Model modes
  • Fallback replies and handoff workflows cover edge cases gracefully.
  • 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)
  • Lets you tweak everything—KnowledgeBase weight, retrieval params, system prompts—for deep control.
  • Encourages devs to swap embedding models or hack the pipeline code as needed.
  • Click “Retrain” to upload new files or re-crawl a site—no tech skills required.
  • Personas and Quick Prompts steer the conversation style; higher plans add custom rules. Persona configuration
  • Run multiple chatbots under one account, each with its own data set.
  • 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
  • Free, MIT-licensed open source—no fees, but you supply the GPUs or cloud servers.
  • Scaling means spinning up more hardware and managing it yourself.
  • Growth plan (~$79/mo), Pro/Scale (~$259/mo), plus an Enterprise tier. View pricing
  • Limits scale with message counts, bots, pages crawled, and file uploads—add-ons boost capacity when needed.
  • 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
  • Entirely local: all docs and chat data stay on your own machine—great for sensitive use cases.
  • No built-in auth or enterprise security—lock things down in your own deployment setup.
  • Uses HTTPS/TLS in transit and encrypted storage at rest—industry-standard security.
  • Data stays in your workspace; formal certifications aren’t front-and-center, but best practices are followed.
  • 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
  • An “Analysis” tab shows which docs were pulled and how the query was built; logs print to the console.
  • No fancy dashboard—add your own logging or monitoring if you need broader stats.
  • Dashboard shows chat histories, analytics, and trends in one place. Dashboard example
  • Daily email digests keep teams updated without logging in.
  • 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
  • Open-source on GitHub; support is community-driven via issues and lightweight docs.
  • Smaller ecosystem: you’re free to fork or extend, but there’s no paid SLA or enterprise help desk.
  • Email support and a “Submit a Request” form for new features or integrations. Submit a request
  • Active blog, Product Hunt launches, and an agency partner program grow the ecosystem.
  • 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
  • Great for offline / on-prem labs where data never leaves the server—perfect for tinkering.
  • Takes more hands-on upkeep and won’t match proprietary giants in sheer capability out of the box.
  • Built-in “Functions” let the bot trigger actions—like opening a support ticket—directly from chat. Learn about Functions
  • SourceSync headless API offers a pure RAG backend when you need more developer control.
  • 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
  • Basic Gradio UI is developer-focused; non-tech users might find the settings overwhelming.
  • No slick, no-code admin—if you need polish or branding, you'll build your own front end.
  • Guided dashboard lets anyone paste a URL or upload files and launch a bot in minutes.
  • Pre-built integrations and a copy-paste embed snippet make deployment a breeze. Embed instructions
  • Live demo plus 7-day free trial means you can test risk-free.
  • 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.
Competitive Positioning
  • Market position: MIT-licensed open-source local RAG solution running entirely on-premises with open-source LLMs (no cloud dependency), designed for developers and tinkerers
  • Target customers: Developers experimenting with RAG locally, organizations with strict data isolation requirements (healthcare, government, defense), and teams wanting complete control without cloud costs or vendor dependencies
  • Key competitors: LangChain/LlamaIndex (frameworks), PrivateGPT, LocalGPT, and cloud RAG platforms for teams needing simplicity
  • Competitive advantages: Completely free and open-source (MIT license) with no fees or subscriptions, 100% local execution keeping all data on-premises, full control over model choice (any Hugging Face model), Python-based with full source code access for customization, "Retrieval Tuning Module" for transparency into answer generation, and zero external dependencies beyond local compute
  • Pricing advantage: Completely free with MIT license; only cost is GPU hardware or cloud compute; best value for teams with existing GPU infrastructure wanting to avoid subscription costs; requires technical expertise and hands-on maintenance
  • Use case fit: Ideal for offline/air-gapped environments requiring complete data isolation (defense, healthcare with strict PHI requirements), developers learning RAG internals and experimenting locally, and organizations with GPU infrastructure wanting zero cloud costs and complete control over LLM stack without vendor dependencies
  • Market position: User-friendly no-code RAG chatbot platform emphasizing rapid website crawling and multi-channel support for SMB customer service teams
  • Target customers: Small to mid-size businesses needing quick website-based chatbot deployment, support teams requiring native channel integrations (Slack, Google Chat, Messenger, Zendesk, Freshchat), and companies wanting 95+ language support with minimal technical overhead
  • Key competitors: Chatbase.co, Botsonic, Ragie.ai, WonderChat, and other no-code chatbot builders targeting SMB market
  • Competitive advantages: Comprehensive website crawling (up to 100K pages on Enterprise), native integrations with 10+ support/messaging platforms, GPT-4o/GPT-4o-mini model selection, "Functions" feature enabling bot actions (support tickets, CRM updates), headless SourceSync API for custom RAG backends, 95+ language support, and white-label option for seamless branding
  • Pricing advantage: Mid-range at ~$79/month (Growth) and ~$259/month (Pro/Scale); straightforward tiered pricing without confusing add-ons; scales with message counts and page limits; best value for growing SMBs needing multi-channel presence without per-interaction charges
  • Use case fit: Ideal for businesses wanting to quickly convert website content into chatbot knowledge base, support teams needing native integrations with multiple messaging platforms (Slack, Messenger, Zendesk, Freshchat), and SMBs requiring no-code setup with webhook automation for CRM/ticketing workflows without developer resources
  • 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
  • Default Model: WizardVicuna-13B-Uncensored (instruction-fine-tuned open-source model)
  • Hugging Face Compatibility: Swap in any Hugging Face model with sufficient GPU resources (Llama 2, Falcon, Mistral, etc.)
  • Full Local Control: Models run entirely on-premises with no external API calls or cloud dependencies
  • Embedding Model: Default multilingual-e5-base for retrieval with option to swap for other embedding models
  • Model Customization: Fine-tune or quantize models for specific use cases and hardware constraints
  • No Vendor Lock-In: Complete flexibility to use any open-source LLM without subscription fees or API limits
  • GPU Requirements: Smaller models may not match GPT-4 depth but enable complete data isolation and zero operational costs
  • GPT-4o (Full Model): OpenAI's flagship multimodal model for deeper, more nuanced answers with comprehensive reasoning
  • GPT-4o-mini: Faster, cost-optimized variant balancing speed and quality for high-volume deployments
  • Model Selection Per Chatbot: Choose model independently for each bot to optimize cost/performance trade-offs
  • ChatGPT API (GPT-3.5-turbo): Default model for all chatbots on lower-tier plans providing fast, accurate responses
  • GPT-4 Availability: Available on Pro and Elite pricing plans for advanced use cases requiring deeper reasoning
  • No Custom Models: Limited to OpenAI models—no support for Claude, Gemini, Llama, or custom fine-tuned models
  • Automatic Updates: Benefits from OpenAI model improvements without manual configuration changes
  • 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
R A G Capabilities
  • Retrieval-Centric Generation (RCG): Research-backed approach explicitly separating LLM roles from knowledge memorization for more efficient implementation
  • Retrieval Tuning Module: Transparency into answer generation showing which documents were retrieved and how queries were built
  • Mixtures-of-Knowledge-Bases (MoKB): Multiple selectable knowledge bases with intelligent routing between knowledge sources
  • Explicit Prompt-Weighting (EPW): Control over retrieved knowledge base weighting in final answer generation
  • FAISS Vector Search: Fast approximate nearest neighbor search using Facebook's FAISS library for efficient retrieval
  • On-the-Fly Knowledge Base Creation: Drag-and-drop documents in GUI to create knowledge bases without manual preprocessing
  • Analysis Tab: Visual debugging showing document retrieval process and query construction for transparency
  • Multiple Document Support: Handles PDFs, text files, DOCX, PPTX, HTML, and other common formats
  • Website Crawling: Crawls entire websites by URL or sitemap with support for thousands of pages in single operation
  • Retrieval-Augmented Generation: Grounds AI responses in uploaded/crawled content to minimize hallucinations and ensure factual accuracy
  • File Upload Support: CSV, TXT, PDF, DOCX, PPTX, Markdown (10MB per file) for knowledge base augmentation
  • Cloud Storage Connectors: Google Drive, Dropbox, OneDrive, Notion, Confluence, GitBook direct integration for automated content syncing
  • Enterprise Scale: Up to 100,000 pages on Enterprise tier for large content libraries
  • Manual Retraining: Click-button retraining with automated retrain cycles on roadmap for future releases
  • Multi-Turn Context: Conversation history retained across turns for coherent, context-aware interactions
  • Fallback Handling: Graceful degradation when knowledge base doesn't contain answer with customizable fallback responses
  • 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
Use Cases
  • Air-Gapped Environments: Defense, classified research, and secure facilities requiring complete offline operation without external connectivity
  • Healthcare PHI Compliance: HIPAA-regulated organizations needing 100% data isolation for protected health information
  • RAG Research & Education: Developers learning RAG internals with full visibility into retrieval and generation processes
  • Local Experimentation: Prototype RAG applications locally before committing to cloud infrastructure and subscription costs
  • Data Sovereignty: Organizations with strict data residency requirements preventing cloud storage or processing
  • Zero-Cost RAG: Teams with existing GPU infrastructure wanting to avoid subscription fees for RAG capabilities
  • Custom Model Development: Research teams fine-tuning and testing custom LLMs and embedding models for specific domains
  • Customer Support Automation: 24/7 instant answers from website/documentation reducing support ticket volume
  • Website Knowledge Conversion: Rapidly convert existing website content into interactive chatbot knowledge base
  • Multi-Channel Support: Unified bot across website, Slack, Google Chat, Facebook Messenger, Zendesk, Freshchat
  • Lead Generation: Automatic lead capture during chat sessions with CRM integration via webhooks
  • Global Support Teams: 95+ language support enabling worldwide customer service with single bot
  • SaaS Onboarding: Interactive product documentation and onboarding assistance for new users
  • E-Commerce Support: Product information, shipping policies, and order assistance with "Functions" for ticket creation
  • Internal Knowledge Base: Employee self-service for HR policies, IT documentation, and company procedures
  • 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)
  • Financial services: Product guides, compliance documentation, customer education with GDPR compliance
  • E-commerce: Product recommendations, order assistance, customer inquiries with API integration to 5,000+ apps via Zapier
  • SaaS onboarding: User guides, feature explanations, troubleshooting with multi-agent support for different teams
Security & Compliance
  • 100% Local Execution: All data and processing stays on-premises with zero external transmission or cloud dependencies
  • No Third-Party APIs: No external API calls to OpenAI, Anthropic, or other cloud LLM providers
  • Complete Data Isolation: Ideal for classified, PHI, PII, or confidential data requiring air-gapped processing
  • No Built-In Authentication: Security implementation is user responsibility in deployment environment
  • Open-Source Auditing: MIT license with full source code transparency for security reviews and compliance validation
  • Self-Managed Security: Organization controls all security layers (network, authentication, encryption, access control)
  • Compliance Flexibility: Can be configured to meet HIPAA, FedRAMP, GDPR, or other regulatory requirements through deployment architecture
  • HTTPS/TLS Encryption: Industry-standard encryption for data in transit between users and chatbot
  • Encrypted Storage: Data at rest protected with encryption in SiteGPT's cloud infrastructure
  • Workspace Isolation: Customer data stays isolated within individual workspaces
  • No Formal Certifications Disclosed: SOC 2, ISO 27001, HIPAA compliance not publicly documented
  • Best Practices Implementation: Follows industry security standards for SaaS platforms
  • Data Privacy: Customer content used only for chatbot training and responses, not for model improvement
  • Access Controls: User authentication and workspace-level permissions for team collaboration
  • Limited Compliance Documentation: May not meet requirements for highly regulated industries (healthcare, finance) without additional validation
  • 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
  • Completely Free: MIT open-source license with no subscription fees, API charges, or usage limits
  • Infrastructure Costs Only: GPU hardware or cloud compute (AWS/GCP/Azure GPU instances) are the only expenses
  • No Per-Query Charges: Unlimited queries without per-request pricing or rate limits
  • No Vendor Fees: Zero payments to SaaS providers or LLM API vendors (OpenAI, Anthropic, etc.)
  • GPU Requirements: Single GPU sufficient for development; scale hardware based on throughput needs
  • Open-Source Ecosystem: Leverage free Hugging Face models, FAISS library, and PyTorch without licensing costs
  • Best Value For: Teams with existing GPU infrastructure or ability to provision cloud GPU instances economically
  • Growth Plan: ~$79/month with website crawling, file uploads, basic integrations, and GPT-3.5-turbo
  • Pro/Scale Plan: ~$259/month adding GPT-4 access, higher message limits, advanced integrations, webhook support
  • Enterprise Plan: Custom pricing for 100K+ pages, white-label branding, dedicated support, and volume discounts
  • 7-Day Free Trial: Risk-free evaluation without credit card requirement
  • No Free Plan: Trial only; requires paid subscription after evaluation period
  • Scalable Limits: Message counts, bots, pages crawled, and file uploads scale with tier selection
  • Add-Ons Available: Boost capacity beyond plan limits when needed for seasonal traffic spikes
  • Straightforward Pricing: Tiered structure without confusing per-interaction charges or hidden fees
  • 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
  • GitHub Repository: Open-source at github.com/RCGAI/SimplyRetrieve with code, documentation, and examples
  • Research Paper: Academic publication on arXiv (2308.03983) explaining RCG approach and architecture
  • Community Support: GitHub Issues for bug reports, feature requests, and community troubleshooting
  • Lightweight Documentation: README and docs directory with setup instructions and usage examples
  • No Paid Support: Community-driven support only; no SLAs or enterprise help desk available
  • Code Examples: Example scripts and Jupyter notebooks demonstrating core functionality
  • Academic Background: Built on established libraries (Hugging Face, Gradio, PyTorch, FAISS) with extensive external documentation
  • Email Support: Submit requests for technical assistance and feature questions
  • "Submit a Request" Form: Dedicated channel for integration requests and feature suggestions
  • REST API Documentation: API reference for bot management, content uploads, and answer retrieval
  • Active Blog: Product updates, use cases, and best practices published regularly
  • Product Hunt Community: User reviews, feedback, and feature discussions on Product Hunt platform
  • Agency Partner Program: Ecosystem for agencies building chatbots for clients
  • Guided Dashboard: Intuitive interface with tooltips and onboarding guidance for new users
  • No Dedicated Support Team: Higher tiers may include priority support but not extensively documented
  • 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
  • Open-source resources: Python SDK (customgpt-client), Postman collections, GitHub integrations Open-Source SDK
  • Active community: User community plus 5,000+ app integrations through Zapier ecosystem
  • Regular updates: Platform stays current with ongoing GPT and retrieval improvements automatically
Limitations & Considerations
  • Developer-Only Tool: Requires Python expertise, GPU knowledge, and technical setup—not suitable for non-technical users
  • GPU Infrastructure Required: Needs dedicated GPU hardware or cloud GPU instances with associated costs and management overhead
  • Basic UI: Gradio interface is functional but not polished—requires custom front-end development for production use
  • Limited Scalability: Scaling requires manual infrastructure management and load balancing vs auto-scaling cloud platforms
  • No Enterprise Features: Missing multi-tenancy, user management, advanced analytics, and production-grade monitoring
  • Slower Inference: Open-source models on single GPU (few to 10+ seconds per reply) vs sub-second cloud API responses
  • Manual Knowledge Base Updates: No automatic web crawling, syncing, or scheduled reindexing capabilities
  • No Pre-Built Integrations: Requires custom development to integrate with Slack, websites, or support platforms
  • Limited Context Memory: Primarily single-turn Q&A with minimal conversation history retention
  • Maintenance Burden: User responsible for updates, model management, troubleshooting, and infrastructure maintenance
  • OpenAI-Only Models: Limited to GPT models—no Claude, Gemini, Llama, or custom model support
  • Manual Retraining: No automatic content syncing yet—requires manual button-click to update knowledge base
  • 10MB File Size Limit: Per-file upload cap may constrain large document processing vs competitors with higher limits
  • No Formal Compliance Certifications: SOC 2, ISO 27001, HIPAA not publicly documented—may limit enterprise adoption
  • Limited Advanced RAG Features: Missing knowledge graphs, hybrid search, or advanced retrieval tuning found in enterprise platforms
  • No Multi-LLM Support: Cannot compare or route between multiple model providers for optimal responses
  • Webhook-Only Integrations: Advanced integrations require webhook development on higher tiers
  • No On-Premise Deployment: Cloud-only SaaS with no self-hosting option for air-gapped or highly regulated environments
  • Limited Analytics Depth: Dashboard and daily digests provide basic metrics but lack advanced product analytics or A/B testing
  • SMB-Focused: Feature set optimized for small/mid-size businesses—may lack enterprise-grade controls and customization
  • 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
Core Agent Features
  • Retrieval-Centric Generation (RCG): Research-backed approach separating LLM reasoning capabilities from knowledge memorization—more efficient than traditional RAG architectures
  • Retrieval Tuning Module: Developer-focused transparency layer showing which documents were retrieved, how queries were constructed, and how answers were generated
  • Knowledge Base Mixing (MoKB): Route queries across multiple selectable knowledge bases with intelligent source selection and weighting
  • Explicit Prompt Weighting (EPW): Fine-grained control over retrieved knowledge base influence in final answer generation
  • Single-Turn Q&A Focus: Primarily designed for single-turn question answering—limited multi-turn conversation and context memory
  • Analysis Tab Transparency: Visual debugging interface showing document retrieval process and query construction for answer inspection
  • Local Agent Execution: All agent processing happens on-premises with zero external API calls—complete control over agent behavior and data
  • LIMITATION - No Chatbot UI: Gradio interface for developers only—no polished conversational interface for end users or production deployment
  • LIMITATION - No Lead Capture: No built-in lead generation, email collection, or CRM integration capabilities—manual implementation required
  • LIMITATION - No Human Handoff: No escalation workflows, live agent transfer, or fallback mechanisms for complex queries—developer must build these features
  • LIMITATION - No Multi-Channel Support: No native integrations with Slack, Teams, WhatsApp, or website widgets—requires custom wrapper development
  • LIMITATION - No Session Management: Stateless interactions without conversation history tracking or multi-turn context retention
  • Multi-Turn Conversation: Maintains conversation history visible in admin dashboard for coherent context-aware multi-turn interactions
  • Sentiment Tracking: Real-time sentiment analysis and conversation metrics monitoring for performance optimization and customer insights
  • Lead Collection System: Automatic lead capture during chat sessions with industry-specific templates (SaaS, E-commerce, Professional Services) and customizable trigger keywords
  • Human Handoff Integration: Built-in escalation workflows allowing users to seamlessly transition to live agents with button-click transfers when AI cannot handle queries
  • Functions Framework: Enable bots to trigger external actions (support tickets, CRM updates, booking workflows) directly from chat conversations without leaving interface
  • Native Channel Integrations: Pre-built connectors for Slack, Google Chat, Facebook Messenger, Crisp, Freshchat, Zendesk Chat, Zoho SalesIQ enabling multi-channel agent deployment
  • 24/7 Lead Capture: Weekend browsers, late-night emergencies, holiday shoppers—captures and qualifies leads around the clock even while team sleeps
  • Webhook Automation: Higher tiers add webhook support for event-driven CRM/ticketing system integration and workflow automation
  • Email Notifications: Lead collection emails sent to chatbot owner with optional custom email recipients for distributed team notifications
  • Custom Lead Fields: Unlimited custom fields with Custom template for capturing industry-specific information (project scope, timelines, business requirements)
  • Trigger Customization: Configure lead forms to display on specific keywords (pricing, demo, consultation) or after set number of conversation exchanges (1-20 messages)
  • 95+ Language Support: Multilingual agent capabilities handling diverse global customer bases without separate language-specific configurations
  • Analytics Dashboard: Comprehensive conversation tracking, chat history analysis, and performance trends in centralized dashboard with daily email summaries
  • AI Conversation Analysis: Tools to analyze chatbot conversations with AI to uncover knowledge gaps, user intent patterns, and actionable improvements
  • 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
R A G-as-a- Service Assessment
  • Platform Type: NOT A RAG-AS-A-SERVICE PLATFORM - Open-source academic research project for local Retrieval-Centric Generation experimentation and learning
  • Core Mission: Provide localized, lightweight, user-friendly interface to Retrieval-Centric Generation (RCG) approach for machine learning community exploration and research
  • Academic Foundation: Published research tool from RCGAI with arXiv paper (2308.03983) explaining RCG methodology and architectural design decisions
  • Target Market: Researchers, developers, and organizations experimenting with RAG locally without cloud dependencies—NOT commercial service users
  • Self-Hosted Infrastructure: MIT-licensed tool requiring user-managed GPU hardware or cloud compute—no managed infrastructure, APIs, or service-level agreements
  • Developer-First Design: Python-based with Gradio GUI and script execution—intended for technical users comfortable with GPU infrastructure and model management
  • RAG Implementation: Retrieval-Centric Generation (RCG) philosophy emphasizing retrieval over memorization—FAISS vector search with open-source LLMs (WizardVicuna-13B default, any Hugging Face model supported)
  • API Availability: NO formal REST API or SDKs—interaction via Python scripts and local Gradio interface requiring subprocess calls or custom wrappers
  • Data Privacy Advantage: 100% local execution with zero external transmission—ideal for classified, PHI, PII, or confidential data requiring air-gapped processing
  • Pricing Model: Completely free (MIT license) with no subscription fees—only cost is GPU hardware or cloud compute infrastructure
  • Support Model: Community-driven GitHub Issues and lightweight documentation—no paid support, SLAs, or customer success teams
  • LIMITATION vs Managed Services: NO managed infrastructure, automatic scaling, production-grade monitoring, enterprise security controls, or commercial support—users responsible for all operational aspects
  • LIMITATION - No Service Features: NO authentication systems, multi-tenancy, user management, analytics dashboards, or SaaS conveniences—pure research/development tool
  • Comparison Validity: Architectural comparison to commercial RAG-as-a-Service platforms like CustomGPT.ai is MISLEADING—SimplyRetrieve is open-source research tool for on-premises experimentation, not production service
  • Use Case Fit: Perfect for offline/air-gapped RAG research, developers learning RAG internals with full transparency, organizations with strict data isolation requirements (defense, healthcare PHI compliance), and teams wanting zero cloud costs with existing GPU infrastructure
  • Platform Type: NO-CODE CHATBOT BUILDER WITH RAG - SMB-focused conversational AI platform emphasizing rapid deployment over pure RAG infrastructure
  • Core Mission: Enable small to mid-size businesses to quickly convert website content into chatbot knowledge base with multi-channel support and minimal technical overhead
  • Target Market: SMB customer service teams, support departments, and agencies building chatbots for clients—NOT primarily developer or RAG infrastructure market
  • RAG Implementation: Retrieval-augmented generation for grounding responses in crawled/uploaded content with fallback handling—focused on accuracy over advanced RAG techniques
  • API Availability: REST API for bot management, content uploads, and answer retrieval—BUT platform emphasizes no-code dashboard over API-first development
  • Managed Service: Fully hosted SaaS with guided dashboard, pre-built integrations, and 7-day free trial—no infrastructure management required
  • Pricing Model: Tiered subscription (~$79/month Growth, ~$259/month Pro/Scale, custom Enterprise) scaling with message counts, bots, and page limits
  • Data Sources: Website crawling (up to 100K pages Enterprise), file uploads (CSV, TXT, PDF, DOCX, PPTX, Markdown 10MB limit), cloud storage connectors (Google Drive, Dropbox, OneDrive, Notion, Confluence, GitBook)
  • Model Support: OpenAI GPT-4o/GPT-4o-mini selection only—no multi-model support, Claude, Gemini, or custom models
  • White-Label Option: Remove SiteGPT branding for seamless customer-facing deployment (add-on feature)
  • Support Model: Email support, "Submit a Request" form, active blog, Product Hunt community, agency partner program—standard SaaS support without dedicated teams on lower tiers
  • Security Posture: HTTPS/TLS encryption, encrypted storage, workspace isolation—NO formal SOC 2, ISO 27001, or HIPAA certifications publicly disclosed
  • LIMITATION - Not Pure RAG-as-a-Service: Platform combines chatbot building with RAG capabilities—not dedicated RAG infrastructure API like Ragie.ai or Pinecone Assistant
  • LIMITATION - Manual Retraining: No automatic content syncing or scheduled reindexing—requires manual button-click to update knowledge base when sources change
  • LIMITATION - Limited RAG Features: Missing advanced capabilities like hybrid search, reranking, knowledge graphs, multi-query fusion found in enterprise RAG platforms
  • Comparison Validity: Comparison to pure RAG-as-a-Service platforms requires context—SiteGPT emphasizes no-code chatbot deployment with RAG vs developer-focused RAG infrastructure APIs
  • Use Case Fit: Perfect for SMBs wanting quick website-based chatbot deployment, support teams needing native multi-channel integrations (Slack, Messenger, Zendesk), and agencies building chatbots for clients without coding—NOT ideal for developers needing flexible RAG infrastructure APIs
  • Platform Type: TRUE RAG-AS-A-SERVICE PLATFORM - all-in-one managed solution combining developer APIs with no-code deployment capabilities
  • 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

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Final Thoughts

Final Verdict: SimplyRetrieve vs SiteGPT

After analyzing features, pricing, performance, and user feedback, both SimplyRetrieve and SiteGPT are capable platforms that serve different market segments and use cases effectively.

When to Choose SimplyRetrieve

  • You value completely free and open source
  • Strong privacy focus - fully localized
  • Lightweight - runs on single GPU

Best For: Completely free and open source

When to Choose SiteGPT

  • You value extremely easy setup - minutes to launch
  • Excellent website content training capabilities
  • Seamless integration with major support platforms

Best For: Extremely easy setup - minutes to launch

Migration & Switching Considerations

Switching between SimplyRetrieve and SiteGPT 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

SimplyRetrieve starts at custom pricing, while SiteGPT begins at $49/month. 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

  1. Start with a free trial - Both platforms offer trial periods to test with your actual data
  2. Define success metrics - Response accuracy, latency, user satisfaction, cost per query
  3. Test with real use cases - Don't rely on generic demos; use your production data
  4. Evaluate total cost - Factor in implementation time, training, and ongoing maintenance
  5. Check vendor stability - Review roadmap transparency, update frequency, and support quality

For most organizations, the decision between SimplyRetrieve and SiteGPT 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 15, 2025 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

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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.

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