In this comprehensive guide, we compare Jotform AI Agents and SimplyRetrieve 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 Jotform AI Agents and SimplyRetrieve, 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 Jotform AI Agents if: you value omnichannel excellence: 7 native channels (whatsapp, facebook messenger, instagram, sms, voice/phone, website, standalone) vs most competitors requiring third-party integrations
Choose SimplyRetrieve if: you value completely free and open source
About Jotform AI Agents
Jotform AI Agents is online form builder with ai-powered automation. Form-centric RAG platform with omnichannel reach (WhatsApp, Instagram, SMS, Voice) and 7,000+ templates, built atop Jotform's 35-million-user form builder ecosystem. Runs GPT-4o with confirmed RAG architecture achieving 4.5/5 accuracy rating. Critical gap: NO dedicated AI Agents API for programmatic management—existing REST API covers forms only. $39/month entry, HIPAA/SOC 2/GDPR certified. Best for SMBs needing no-code multi-channel deployment, not developers building custom RAG integrations. Founded in 2006, headquartered in San Francisco, CA, USA, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
88/100
Starting Price
$39/mo
About SimplyRetrieve
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
Key Differences at a Glance
In terms of user ratings, Jotform AI Agents in overall satisfaction. From a cost perspective, SimplyRetrieve offers more competitive entry pricing. The platforms also differ in their primary focus: Form Builder 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
Jotform AI Agents
SimplyRetrieve
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
PDF Uploads: Document knowledge ingestion via PDF format
CRITICAL: CRITICAL GAP - NO Word Documents: .doc/.docx not explicitly supported - PDF uploads only for document ingestion
CRITICAL: CRITICAL GAP - NO Cloud Storage Ingestion: Google Drive, Dropbox, Notion function only as outbound file storage destinations, NOT knowledge sources - cannot auto-sync cloud repositories
Developer Workflow Friction: Must manually download cloud documents before upload vs competitors offering native cloud sync
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.
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.
Multilingual Auto-Detection: 20+ languages with automatic mid-conversation detection and switching to user's preferred language
Human Handoff - 'Take Over Chat': Green dot indicators for active conversations, seamless control transfer, full context preservation
Mobile Push Notifications: iOS/Android app alerts for takeover requests enabling intervention from anywhere
Configurable Escalation Triggers: Automatic flagging based on sentiment analysis, specific keywords, or explicit user requests
Lead Capture: Deep form integration linking to multiple Jotform forms with real-time validation during conversational flows
Payment Collection: 30+ gateway integrations for sales/donations directly within conversations
Conversation History: Fully logged with downloadable PDF transcripts and MP3 audio recordings (voice interactions)
Thumbs Up/Down Feedback: Individual response rating system for continuous improvement
Smart Triggers: Conditional responses based on conversation start, user intent, mentioned topics, sentiment (positive/negative/neutral), keywords, date/time, page URL
Trigger Actions: Show buttons, play videos, display presentations, send emails, create tickets, schedule appointments, start workflows, collect payments
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
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
Visual Customization: Color schemes, gradient backgrounds, font families (Inter, Circular, Times New Roman), chat widget positioning
White-Labeling: Remove Jotform branding from Bronze tier+, full white-label with custom domain URLs (Enterprise only)
Domain Restrictions: Control widget embedding via whitelisting
CRITICAL: CRITICAL LIMITATION - NO Raw CSS Access: All customization flows through visual designer's predefined options - cannot inject custom CSS for pixel-perfect brand matching
Default Gradio interface is pretty plain, with minimal theming.
For a branded UI you’ll tweak source code or build your own front end.
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
Primary Model: OpenAI GPT-4o for all standard accounts
HIPAA-Compliant Model: Google Gemini via Vertex AI exclusively for Gold/Enterprise accounts with BAA
Confirmed RAG Implementation: "Jotform utilizes the RAG technique to ensure all generated responses...are based on accurate, verified information from an agent's knowledge base"
Hallucination Prevention: RAG grounding + continuous monitoring of user-flagged responses with development team review
Third-Party Validation: 4.5/5 accuracy and reliability rating, 4.6/5 performance and speed (Futurepedia)
CRITICAL: NO Model Selection: Users CANNOT choose between providers or bring own API keys - Jotform manages routing internally
CRITICAL: NO Model Switching: Locked to GPT-4o (or Gemini for HIPAA) with no flexibility for cost/quality optimization
NO Benchmark Transparency: No published hallucination rates, retrieval accuracy percentages, or latency metrics - relies on third-party ratings only
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.
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)
CRITICAL: CRITICAL LIMITATION - NO AI Agents API: No dedicated API for programmatically creating, managing, or querying AI agents
Jotform REST API: Exists at api.jotform.com but covers forms and form submissions ONLY, NOT AI agents
Cannot Perform Programmatically: Create agents, upload/update knowledge bases, query agents through API endpoints, integrate agent conversations into custom applications beyond embedding
Outbound API Capability: Agents can send requests to external webhooks/APIs based on conversation triggers (ticket creation, CRM updates) - agent-to-external-system direction only
11 SDKs Available: Python, JavaScript, PHP, Java, Go, C#, Ruby, Scala, iOS, Android, NodeJS - forms API coverage ONLY, NOT AI agents
Documentation: api.jotform.com/docs provides comprehensive code samples for forms - NO technical API reference for AI agents
Architectural Positioning: Platform designed as no-code consumer tool, NOT developer toolkit or RAG-as-a-Service API
Developer Gap: Fundamentally limits Jotform AI Agents to visual builder use cases vs programmatic integration workflows
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.
Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat.
API Documentation
Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
Performance & Accuracy
Futurepedia Third-Party Ratings: 4.5/5 accuracy and reliability, 4.6/5 performance and speed
RAG Grounding: Responses based on verified knowledge base information vs general model knowledge
Continuous Monitoring: Development team reviews AI-flagged responses for negative feedback to enhance detection tools
Feedback System: Thumbs up/down on individual responses enables ongoing improvement
Hallucination Prevention: RAG technique + user feedback monitoring for accuracy maintenance
24/7 Availability: All deployment channels support continuous operation
99.9% Uptime SLA: Enterprise tier with service level guarantees
Hourly Replication: Google Cloud and AWS backup infrastructure with data redundancy
CRITICAL: NO Published Benchmarks: No quantitative hallucination rates, retrieval accuracy percentages, or latency metrics - transparency gap vs competitors
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.
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.
WhatsApp Business: Bidirectional messaging, multi-language support, media sharing with full chatbot functionality
Instagram Integration (Enterprise): DM replies, comment responses, story reply automation - social commerce strength
Voice Capabilities: Dedicated phone numbers ($10/month), inbound call handling, web voice calls, website voice chat with customizable accents/gender/tone
SMS Platform: Dedicated numbers with NLP-powered text conversations (250 SMS free tier scaling with plans)
Standalone Chat: Shareable links, QR codes, progressive web app conversion for kiosk mode deployments
Website Embedding: 5 styles (page embed, chatbot bubble, lightbox, popup, WordPress shortcode) with positioning control
Twilio Integration: Custom phone number routing options for advanced voice deployments
Competitive Advantage: Most competitors require third-party integrations or Zapier for multi-channel - Jotform offers native depth
N/A
N/A
Voice & Phone Capabilities ( Differentiator)
Dedicated Phone Numbers: $10/month per number with full agent functionality
Inbound Call Handling: Agents answer phone calls with conversational AI responses
Web Voice Calls: Make voice calls directly from web interface
Website Voice Chat: Add voice interaction to website chatbots
Voice Customization: Customizable accents, gender options, tone settings for natural conversations
Twilio Integration: Advanced routing and custom number porting options
Voice Forwarding: Route calls to human agents when needed
MP3 Recordings: Downloadable audio logs of voice interactions for quality assurance
Mature Implementation: Voice capabilities more developed than most RAG competitors - unusual market depth
N/A
N/A
Multi- Lingual Support
20+ Languages Supported: English, French, Spanish, German, Japanese, Arabic, Korean, Russian, and more
Automatic Detection: Mid-conversation language switching based on user preference without manual configuration
Separate Settings: Greeting language versus conversation language configuration
Multi-Channel Language Support: Language detection works across WhatsApp, Instagram, SMS, Voice, website, and all deployment channels
Voice Language Options: Accent and language customization for phone/voice channels
Global Deployment: 19 data center options across 15 countries (Enterprise) for regional language optimization
N/A
N/A
R A G-as-a- Service Assessment
Platform Type: FORM-CENTRIC NO-CODE CHATBOT PLATFORM with RAG capabilities - NOT pure RAG-as-a-Service like CustomGPT or Progress
RAG Implementation: Confirmed and explicitly documented - "Jotform utilizes the RAG technique to ensure all generated responses...are based on accurate, verified information from an agent's knowledge base"
Core Identity: Platform positioned as 'form-builder extension' vs developer-first RAG toolkit - fundamentally different target market
CRITICAL: NO AI Agents API: Critical gap - cannot create, manage, or query agents programmatically. Existing REST API covers forms only, NOT AI agents
Developer Limitation: Platform architected for no-code visual builder use cases vs API-first development workflows
Productized Vertical Solution: Exceptional within design parameters (form-to-conversation, multi-channel deployment, templates) but architecturally incompatible with RAG-as-a-Service development patterns
Comparison Validity: Architectural comparison to CustomGPT.ai is LIMITED - both implement RAG but serve fundamentally different use cases (no-code SMB vs developer API platform)
Use Case Fit: Organizations already using Jotform forms (35M+ users), SMBs needing multi-channel deployment without coding, form-to-conversation workflows - NOT developers needing programmatic RAG access
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
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
Market Position: Form-centric no-code chatbot platform with strongest appeal to existing Jotform ecosystem (35M+ users) and non-technical SMB teams
Omnichannel Leadership: 7 native channels (WhatsApp, Instagram, Facebook Messenger, SMS, Voice/Phone, website, standalone) vs most requiring third-party integrations
Form-to-Agent Differentiator: 9.5/10 rated one-click conversion of forms to conversational AI - unique capability absent from pure RAG platforms
Template Library Depth: 7,000+ templates vs minimal/none from RAG-as-a-Service competitors - fastest time to production for standard use cases
Voice Maturity: Dedicated phone numbers, inbound calls, web voice, customizable accents - more developed than most RAG competitors
Pricing Accessibility: $39/month Bronze entry vs $700/month (Progress), $30K+/year (Drift, Yellow.ai) - SMB-friendly with usable free tier
vs. CustomGPT: Jotform excels at no-code multi-channel + form integration vs CustomGPT developer-first RAG API access
vs. Progress: Jotform $39/month + omnichannel vs Progress $700/month + REMi quality monitoring + open-source NucliaDB
vs. Drift: Jotform customer support automation vs Drift B2B sales engagement - different core use cases
vs. Chatling: Jotform form integration + voice vs Chatling 32-model selection + WhatsApp - overlapping SMB market with different strengths
CRITICAL: CRITICAL Developer Gap: NO AI Agents API disqualifies platform for programmatic use cases - form-builder users only
CRITICAL: Cloud Storage Gap: NO Google Drive/Dropbox/Notion knowledge ingestion - manual workflow friction vs competitors
CRITICAL: Model Flexibility Gap: Locked to GPT-4o/Gemini with NO user control vs multi-model competitors (Chatling 32 models, Progress 7 providers)
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: 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
Deployment & Infrastructure
Cloud-Only SaaS: NO on-premise or hybrid deployment options - cloud-hosted exclusively
Primary Infrastructure: Google Cloud (Iowa US, Frankfurt Germany) with AWS backup (Virginia US, Frankfurt Germany)
Hourly Replication: Data backed up hourly across Google Cloud and AWS for redundancy
Enterprise Data Sovereignty: 19 data center options across 15 countries for regional compliance and performance
99.9% Uptime SLA: Enterprise tier with service level guarantees
Website Deployment: 5 embed styles (page, bubble, lightbox, popup, WordPress shortcode) with custom domain support (Enterprise)
Mobile Deployment: iOS and Android apps for agent management (not consumer-facing SDKs)
Progressive Web App: Standalone chat can convert to PWA for kiosk mode deployments
Multi-Channel Infrastructure: Native integrations with WhatsApp Business, Facebook Messenger, Instagram, SMS, Voice maintained by Jotform
NO On-Premise: Air-gapped environments and private infrastructure deployments not supported
N/A
N/A
Unique Capabilities
Form-to-Agent Conversion: One-click transformation of static forms into conversational AI - 9.5/10 rated differentiator
Presentation Agents: AI-narrated slide presentations with live Q&A capabilities
Gmail Agents: Auto-draft email responses in users' Gmail inboxes
Kiosk Mode: Deploy agents as self-service terminals for events and retail with progressive web app conversion
AI Clone: Replicate individual communication styles and personalities - unique personalization capability
Screen Sharing Guidance: Visual step-by-step instructions within conversations
Voice Forwarding: Route phone calls to human agents when AI cannot handle request
Multi-Form Workflows: Link multiple Jotform forms within single conversational flow for complex data collection
Payment Collection: 30+ gateways integrated for in-conversation sales/donations - uncommon in RAG platforms
Approval Workflows: Multi-step approval processes embedded in conversational flows
N/A
N/A
A I Models
Primary Model: OpenAI GPT-4o for all standard accounts - latest and most capable model
HIPAA-Compliant Model: Google Gemini via Vertex AI exclusively for Gold/Enterprise accounts with Business Associate Agreement
RAG Implementation: Confirmed use of Retrieval-Augmented Generation technique for grounded responses based on knowledge base
No Model Selection: Users cannot choose between providers or bring own API keys - Jotform manages routing internally
No Model Switching: Locked to GPT-4o (or Gemini for HIPAA) with no flexibility for cost/quality optimization
Automatic Model Assignment: HIPAA accounts automatically routed to Gemini, standard accounts use GPT-4o
Third-Party Validation: 4.5/5 accuracy and reliability rating, 4.6/5 performance and speed (Futurepedia)
No Benchmark Transparency: No published hallucination rates, retrieval accuracy percentages, or latency metrics
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
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
Confirmed RAG Technique: "Jotform utilizes the RAG technique to ensure all generated responses are based on accurate, verified information from an agent's knowledge base"
Knowledge Base Sources: PDFs, website URLs with auto-recrawl (daily/weekly/monthly), YouTube videos with transcript extraction, PPTX presentations, direct text input, conversational training
Help Desk Sync: Zendesk, Freshdesk, Salesforce Knowledge article imports with automatic recrawling schedules
KB Character Limits: 10M (Free ~2.5K pages), 25M (Bronze ~6.2K), 50M (Silver ~12.5K), 100M (Gold ~25K), unlimited (Enterprise)
Hallucination Prevention: RAG grounding + continuous monitoring of user-flagged responses with development team review
Feedback System: Thumbs up/down on individual responses enables ongoing improvement and accuracy enhancement
No Cloud Storage Ingestion: Google Drive, Dropbox, Notion function only as outbound file storage, NOT knowledge sources
No Word Document Support: .doc/.docx not explicitly supported - PDF uploads only for document ingestion
No Vector Database Control: Embedding models, chunking strategies, or retrieval parameters not exposed to users
Black Box Implementation: No transparency into RAG pipeline internals or optimization 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
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
Form-to-Conversation: Transform static Jotform forms (35M+ user ecosystem) into conversational AI experiences
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: 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)
No Hidden Costs: Transparent pricing with clear overage charges - no credit-based anxiety
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
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
24/7 Live Chat & Email: support@jotform.com with 1-2 hour average response times - significantly faster than industry averages
Public Support Forum: Community Q&A with searchable historical threads for peer assistance
Comprehensive Help Center: jotform.com/help/ai-agents/ with step-by-step tutorials, integration guides, feature-specific articles
Video Tutorials: Visual learning resources supplement written documentation for all skill levels
Enterprise Support: Dedicated customer success managers, scheduled Zoom calls with support teams, SLA-based response guarantees
Professional Services: Implementation, training, and custom development services for Enterprise customers
Mobile App: iOS and Android apps for agent creation, training, management from mobile devices with push notifications
7,000+ Template Library: Healthcare (1,134), customer service (1,050), HR (1,068), education (760) with predefined roles and responses
No Phone Support: Standard plans (Free/Bronze/Silver/Gold) lack phone support - chat and email only
No Dedicated Account Managers: Enterprise tier required for dedicated CSM and scheduled support calls
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
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
Limitations & Considerations
CRITICAL: NO AI Agents API: No dedicated API for programmatically creating, managing, or querying AI agents - major developer limitation
Forms API Only: Existing REST API at api.jotform.com covers forms and form submissions ONLY, NOT AI agents
No Cloud Storage Ingestion: Google Drive, Dropbox, Notion function only as outbound file storage, NOT knowledge sources - critical workflow friction
No Word Document Support: .doc/.docx not explicitly supported - must convert to PDF before upload
No Model Selection: Users CANNOT choose between providers or bring own API keys - Jotform manages routing internally
No Benchmark Transparency: No published hallucination rates, retrieval accuracy percentages, or latency metrics
Limited B2B Messaging: Microsoft Teams & Telegram via Zapier integration only, NO native support
No Raw CSS Access: All customization flows through visual designer's predefined options - cannot inject custom CSS
SOC 2 Enterprise Only: Standard plans lack SOC 2 Type II certification - Enterprise tier required
Platform Positioning: Form-centric no-code chatbot platform with RAG - NOT developer-first RAG toolkit
Analytics Depth: More focused on "conversations + form analytics" vs comprehensive CX suite
Online Interactions Only: Primarily focuses on digital channels - may not suit businesses with significant offline engagement
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
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 Chatbot Features
Autonomous AI Agents: Operate autonomously to perform specific tasks, solve problems, and interact with systems without needing human interaction at every stage - agents figure things out and act on their own
AI Agents Overview
Conversational Form Completion: One of the core features is use of conversational prompts that interactively assist users in completing every field of forms, ensuring accuracy and minimizing errors - unique form-to-conversation capability
Multi-Channel Deployment: AI Agents assist users via multiple channels - chatbot on website, phone, SMS, WhatsApp, QR Code - offering seamless interactions across 7 native platforms
Features Overview
24/7 Availability: AI Agents available around the clock and can handle customer inquiries and questions at any time of day - continuous autonomous operation
Natural Language Understanding: Agents understand customer inquiries and provide immediate, natural responses via web, voice, SMS, WhatsApp enabling human-like conversations
Custom Response Configuration: Set custom responses to frequently asked questions, personalize chatbot questions, and integrate with business's internal data or knowledge base for highly relevant answers
Training & Triggers: Agents trained with data such as FAQs, workflows, user scenarios to enhance responses, with specific triggers and outcomes defined (sending emails, searching websites, creating tickets)
Voice & Phone Capabilities: AI Agents answer questions and assist users via phone with customizable accents, gender, tone settings for natural voice conversations - advanced telephony integration
Human Handoff Excellence: Seamlessly switch from AI chatbot assistance to human agents when needed for exceptional customer service - preserves full context during transition
20+ Language Support: Automatic mid-conversation language detection and switching based on user preference without manual configuration
Lead Capture Integration: Deep form integration linking to multiple Jotform forms with real-time validation during conversational flows for structured data collection
Payment Collection: 30+ gateway integrations (PayPal, Stripe, Square) for in-conversation sales/donations directly within chatbot flows
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.
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.
Additional Considerations
Form-Centric Innovation: Unique positioning transforming static Jotform forms (35M+ user ecosystem) into conversational AI experiences - natural migration path for existing customers
Help Guide
9.5/10 Rated Differentiator: One-click form-to-agent conversion that preserves data validation and structure while enabling natural dialogue - capability absent from pure RAG platforms
SMB Accessibility: $39/month Bronze entry point vs $700+/month enterprise-only competitors - 17x cheaper with genuinely usable free tier (5 agents, 100 conversations)
Voice Maturity: Dedicated phone numbers ($10/month), inbound call handling, web voice calls, customizable accents/gender/tone - more developed than most RAG competitors
Rapid Deployment: "5-minute setup time" using 7,000+ templates (Healthcare 1,134, Customer Service 1,050, HR 1,068, Education 760) with predefined roles and responses
Mobile-First Management: iOS and Android apps for agent creation and management from mobile devices - unusual capability enabling on-the-go administration
NOT a RAG-as-a-Service Platform: Form-centric no-code chatbot platform WITH RAG capabilities - fundamentally different target market (form builders vs RAG developers)
Developer Gap: NO AI Agents API disqualifies platform for programmatic use cases - architected for no-code visual builder workflows, NOT API-first development
Cloud Storage Friction: NO Google Drive/Dropbox/Notion knowledge ingestion - requires manual download-before-upload workflow vs competitors with native cloud sync
Model Inflexibility: Locked to GPT-4o/Gemini with NO user control - cannot bring own API keys or switch models for cost optimization vs multi-model competitors
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.
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.
Final Verdict: Jotform AI Agents vs SimplyRetrieve
After analyzing features, pricing, performance, and user feedback, both Jotform AI Agents and SimplyRetrieve are capable platforms that serve different market segments and use cases effectively.
When to Choose Jotform AI Agents
You value omnichannel excellence: 7 native channels (whatsapp, facebook messenger, instagram, sms, voice/phone, website, standalone) vs most competitors requiring third-party integrations
Form-to-agent conversion rated 9.5/10 differentiator - transforms static data collection into interactive conversation with one click
Best For: Omnichannel excellence: 7 native channels (WhatsApp, Facebook Messenger, Instagram, SMS, Voice/Phone, website, standalone) vs most competitors requiring third-party integrations
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
Migration & Switching Considerations
Switching between Jotform AI Agents and SimplyRetrieve 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
Jotform AI Agents starts at $39/month, while SimplyRetrieve 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 Jotform AI Agents and SimplyRetrieve 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.
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