SimplyRetrieve vs Yellow.ai

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

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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 Yellow.ai 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 Yellow.ai, 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 Yellow.ai if: you value genuinely comprehensive 35+ channel coverage: whatsapp bsp, messenger, instagram, telegram, slack, teams, voice, sms

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 Yellow.ai

Yellow.ai Landing Page Screenshot

Yellow.ai is enterprise conversational ai platform with multi-llm orchestration. Enterprise conversational AI platform with embedded RAG capabilities processing 16 billion+ conversations annually. Multi-LLM orchestration across 35+ channels and 135+ languages with proprietary YellowG LLM claiming <1% hallucination rates. Founded in 2016, headquartered in San Mateo, CA, USA / Bengaluru, India, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
85/100
Starting Price
Custom

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: RAG Platform versus Conversational AI. 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

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SimplyRetrieve
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Yellow.ai
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Data Ingestion & Knowledge Sources
  • File-Based Workflow – Drop PDFs, DOCX, PPTX, HTML into folder and embed via script
  • GUI Knowledge Editor – Add documents on-the-fly through basic interface
  • Manual Processing – ⚠️ No web crawler or automatic refresh capabilities
  • Local Storage – ✅ All data stays on your machine for air-gapped deployments
  • DocCog Engine – 75-85% accuracy with T5 model fine-tuned on SQuAD/TriviaQA
  • Formats – PDF, DOCX, DOC, PPTX, PPT, TXT via platform UI only
  • Enterprise integrations – Salesforce, ServiceNow, Confluence, SharePoint, AWS S3
  • Auto-sync – Hourly, daily, weekly configurable intervals
  • ⚠️ No cloud storage – No Google Drive, Dropbox, or Notion support
  • ⚠️ No API upload – Document management via UI only
  • 1,400+ file formats – PDF, DOCX, Excel, PowerPoint, Markdown, HTML + auto-extraction from ZIP/RAR/7Z archives
  • Website crawling – Sitemap indexing with configurable depth for help docs, FAQs, and public content
  • Multimedia transcription – AI Vision, OCR, YouTube/Vimeo/podcast speech-to-text built-in
  • Cloud integrations – Google Drive, SharePoint, OneDrive, Dropbox, Notion with auto-sync
  • Knowledge platforms – Zendesk, Freshdesk, HubSpot, Confluence, Shopify connectors
  • Massive scale – 60M words (Standard) / 300M words (Premium) per bot with no performance degradation
Integrations & Channels
  • Local Gradio GUI – Python scripts for queries with no pre-built channels
  • No Native Integrations – ⚠️ No Slack, Teams, or website widgets out-of-box
  • Custom Wrappers Required – Build your own connectors to forward messages
  • 35+ channels – WhatsApp (BSP), Messenger, Instagram, Telegram, Slack, Teams, Line
  • Voice channels – IVR, Google Assistant, Amazon Alexa, telephony
  • Enterprise systems – Salesforce, ServiceNow, Confluence, SharePoint
  • Mobile SDKs – Android, iOS, React Native, Flutter, Cordova
  • ⚠️ No Python SDK – Major gap for backend developers
  • Website embedding – Lightweight JS widget or iframe with customizable positioning
  • CMS plugins – WordPress, WIX, Webflow, Framer, SquareSpace native support
  • 5,000+ app ecosystem – Zapier connects CRMs, marketing, e-commerce tools
  • MCP Server – Integrate with Claude Desktop, Cursor, ChatGPT, Windsurf
  • OpenAI SDK compatible – Drop-in replacement for OpenAI API endpoints
  • LiveChat + Slack – Native chat widgets with human handoff capabilities
Core Chatbot Features
  • Open-Source RAG Bot – Runs on local LLMs with streaming responses
  • Single-Turn Q&A – ⚠️ Limited multi-turn conversation and long-term memory
  • Retrieval Tuning Module – Transparency layer showing answer construction process
  • Basic Interactions – No lead capture or human handoff features
  • Multi-turn conversations – Context across turns with intent detection
  • 150+ languages – Automatic detection with native processing
  • Human handoff – Full context transfer with SLA tracking
  • Voice AI – 50+ language support with sentiment analysis
  • 170+ integrations – Complex workflow automation
  • ✅ #1 accuracy – Median 5/5 in independent benchmarks, 10% lower hallucination than OpenAI
  • ✅ Source citations – Every response includes clickable links to original documents
  • ✅ 93% resolution rate – Handles queries autonomously, reducing human workload
  • ✅ 92 languages – Native multilingual support without per-language config
  • ✅ Lead capture – Built-in email collection, custom forms, real-time notifications
  • ✅ Human handoff – Escalation with full conversation context preserved
Customization & Branding
  • Plain Gradio Interface – Minimal theming with developer-focused design
  • Source Code Customization – Tweak code or build custom front-end for branding
  • Visual Studio – Drag-and-drop conversation flow builder
  • White-labeling – Custom branding on Enterprise plan
  • Agent personality – Configurable tone and response style
  • RBAC – Six permission levels for access control
  • Full white-labeling included – Colors, logos, CSS, custom domains at no extra cost
  • 2-minute setup – No-code wizard with drag-and-drop interface
  • Persona customization – Control AI personality, tone, response style via pre-prompts
  • Visual theme editor – Real-time preview of branding changes
  • Domain allowlisting – Restrict embedding to approved sites only
L L M Model Options
  • WizardVicuna-13B Default – Instruction-tuned open-source model included
  • Hugging Face Compatible – Swap any model with sufficient GPU resources
  • Full Local Control – ✅ No external APIs or cloud dependencies
  • Model Limitations – ⚠️ Smaller models won't match GPT-4 depth
  • YellowG LLM – Proprietary with <1% hallucination claims, 0.6s response
  • Komodo-7B – Indonesia-focused with 11+ regional languages
  • T5 Fine-Tuned – SQuAD/TriviaQA for Q&A extraction
  • GPT-3/3.5 – Integration documented
  • ⚠️ GPT-4/Claude unclear – Not explicitly confirmed in docs
  • ⚠️ No manual selection – Dynamic routing handles automatically
  • GPT-5.1 models – Latest thinking models (Optimal & Smart variants)
  • GPT-4 series – GPT-4, GPT-4 Turbo, GPT-4o available
  • Claude 4.5 – Anthropic's Opus available for Enterprise
  • Auto model routing – Balances cost/performance automatically
  • Zero API key management – All models managed behind the scenes
Developer Experience ( A P I & S D Ks)
  • Python Script Interface – No formal REST API or SDK
  • Subprocess Integration – Call scripts directly or build custom wrapper
  • Open Source Access – ✅ Full code access for modification
  • Platform-first – APIs supplementary, not primary access
  • Available via API – User management, event pushing, webhooks
  • Mobile SDKs – Well-documented Android, iOS, React Native, Flutter
  • ⚠️ NOT via API – Bot creation, document upload, RAG querying
  • ⚠️ No Python SDK – Only mobile SDKs available
  • REST API – Full-featured for agents, projects, data ingestion, chat queries
  • Python SDK – Open-source customgpt-client with full API coverage
  • Postman collections – Pre-built requests for rapid prototyping
  • Webhooks – Real-time event notifications for conversations and leads
  • OpenAI compatible – Use existing OpenAI SDK code with minimal changes
Performance & Accuracy
  • Slower Inference – ⚠️ 3-10+ seconds per reply on single GPU
  • Decent Accuracy – Good when relevant docs found, struggles with complexity
  • FAISS Vector Search – Fast retrieval using Facebook's library
  • YellowG claims – <1% hallucination vs GPT-3's 22.7%
  • 0.6s latency – Average response time claimed
  • DocCog accuracy – 75-85% depending on complexity
  • Scale validated – 16B+ conversations annually
  • ⚠️ No published benchmarks – No independent validation
  • Sub-second responses – Optimized RAG with vector search and multi-layer caching
  • Benchmark-proven – 13% higher accuracy, 34% faster than OpenAI Assistants API
  • Anti-hallucination tech – Responses grounded only in your provided content
  • OpenGraph citations – Rich visual cards with titles, descriptions, images
  • 99.9% uptime – Auto-scaling infrastructure handles traffic spikes
Customization & Flexibility ( Behavior & Knowledge)
  • Deep Parameter Control – Tweak retrieval params, system prompts, knowledge weighting
  • Embedding Model Swap – Replace multilingual-e5-base with alternatives
  • Pipeline Modification – ✅ Full source access for custom logic
  • Agent persona – Name, role, tone, communication style
  • Conversation rules – Custom behavior for specific situations
  • Multi-KB support – Role-based access, cross-KB search
  • ⚠️ No embedding control – Retrieval mechanisms not exposed
  • ⚠️ No programmatic API – UI-only knowledge management
  • Live content updates – Add/remove content with automatic re-indexing
  • System prompts – Shape agent behavior and voice through instructions
  • Multi-agent support – Different bots for different teams
  • Smart defaults – No ML expertise required for custom behavior
Pricing & Scalability
  • MIT Licensed – ✅ Completely free with no subscription fees
  • Infrastructure Costs – Pay only for GPU hardware or cloud servers
  • Manual Scaling – ⚠️ Spin up and manage your own hardware
  • Free tier – 1 bot, 2 channels, 100 MTUs (evaluation only)
  • Basic – ~$10,000/year for single use case
  • Standard – ~$25,000/year for up to 4 use cases
  • Enterprise – Custom with unlimited bots, on-premise options
  • ⚠️ 4-month implementation – Typical deployment timeline
  • Standard: $99/mo – 60M words, 10 bots
  • Premium: $449/mo – 300M words, 100 bots
  • Auto-scaling – Managed cloud scales with demand
  • Flat rates – No per-query charges
Security & Privacy
  • 100% Local Execution – ✅ Perfect for sensitive data and air-gapped environments
  • No External Transmission – All processing stays on-premises
  • DIY Security – ⚠️ No built-in auth, you implement access controls
N/A
  • SOC 2 Type II + GDPR – Third-party audited compliance
  • Encryption – 256-bit AES at rest, SSL/TLS in transit
  • Access controls – RBAC, 2FA, SSO, domain allowlisting
  • Data isolation – Never trains on your data
Observability & Monitoring
  • Analysis Tab – Shows retrieved docs and query construction process
  • Console Logging – Basic logs printed to terminal
  • No Dashboard – ⚠️ Add your own monitoring for stats
  • Analytics dashboard – Comprehensive conversation metrics
  • Deflection metrics – Automation success rates
  • Voice analytics – IVR and telephony tracking
  • 15-day audit logs – API activity retention
  • Real-time dashboard – Query volumes, token usage, response times
  • Customer Intelligence – User behavior patterns, popular queries, knowledge gaps
  • Conversation analytics – Full transcripts, resolution rates, common questions
  • Export capabilities – API export to BI tools and data warehouses
Support & Ecosystem
  • Community-Driven – GitHub issues and lightweight documentation
  • Research Foundation – Academic paper (arXiv 2308.03983) on RCG approach
  • No Paid Support – ⚠️ No SLA or enterprise help desk
  • Multi-channel support – Email, chat, phone with tier-based access
  • Enterprise support – Dedicated CSMs, priority SLAs
  • Gartner recognition – Magic Quadrant 'Challenger' (2023/2025)
  • G2 ratings – 4.4/5 (106 reviews), 9.3 customization
  • ⚠️ Steep learning curve – "Rubik's cube blindfolded" G2 review
  • Comprehensive docs – Tutorials, cookbooks, API references
  • Email + in-app support – Under 24hr response time
  • Premium support – Dedicated account managers for Premium/Enterprise
  • Open-source SDK – Python SDK, Postman, GitHub examples
  • 5,000+ Zapier apps – CRMs, e-commerce, marketing integrations
A I Models
  • WizardVicuna-13B – Default uncensored instruction-tuned model
  • Any Hugging Face Model – Llama 2, Falcon, Mistral with GPU capacity
  • No Vendor Lock-In – ✅ Complete flexibility without API limits
  • Performance Trade-Off – ⚠️ Open models slower than managed cloud APIs
  • YellowG LLM – Proprietary with <1% hallucination claims
  • Komodo-7B – 11+ Indonesian language variants
  • Orchestrator LLM – Context switching, multi-intent detection
  • T5 Fine-Tuned – DocCog Q&A extraction
  • ⚠️ Limited flexibility – No manual model selection
  • OpenAI – GPT-5.1 (Optimal/Smart), GPT-4 series
  • Anthropic – Claude 4.5 Opus/Sonnet (Enterprise)
  • Auto-routing – Intelligent model selection for cost/performance
  • Managed – No API keys or fine-tuning required
R A G Capabilities
  • Retrieval-Centric Generation – Research-backed approach separating LLM from knowledge memorization
  • Mixtures-of-Knowledge-Bases – Multiple knowledge bases with intelligent routing
  • Explicit Prompt-Weighting – Control retrieved content influence on answers
  • Retrieval Transparency – ✅ Visual debugging showing document selection
  • FAISS Search – Fast approximate nearest neighbor retrieval
  • Agentic RAG – Multi-checkpoint validation with guardrails
  • DocCog – 75-85% accuracy for Q&A extraction
  • Hallucination prevention – Proprietary training approach
  • Knowledge sync – Configurable intervals for external sources
  • ⚠️ Closed architecture – No direct API or embedding access
  • GPT-4 + RAG – Outperforms OpenAI in independent benchmarks
  • Anti-hallucination – Responses grounded in your content only
  • Automatic citations – Clickable source links in every response
  • Sub-second latency – Optimized vector search and caching
  • Scale to 300M words – No performance degradation at scale
Use Cases
  • Air-Gapped Environments – ✅ Defense, classified research requiring offline operation
  • Healthcare PHI Compliance – HIPAA organizations needing 100% data isolation
  • RAG Research – Developers learning internals with full transparency
  • Zero-Cost RAG – Teams with GPU infrastructure avoiding subscriptions
  • Data Sovereignty – Strict data residency preventing cloud processing
  • Customer service – 90% automation across 35+ channels
  • Employee experience – IT support, HR FAQs, leave applications
  • E-commerce – Shopping assistance, order tracking, fraud detection
  • Regulated industries – Healthcare, financial services, government
  • Customer support – 24/7 AI handling common queries with citations
  • Internal knowledge – HR policies, onboarding, technical docs
  • Sales enablement – Product info, lead qualification, education
  • Documentation – Help centers, FAQs with auto-crawling
  • E-commerce – Product recommendations, order assistance
Security & Compliance
  • Complete Data Isolation – ✅ Ideal for classified, PHI, PII data
  • No Third-Party APIs – Zero external calls to cloud providers
  • Open-Source Auditing – Full code transparency for security reviews
  • Self-Managed Security – ⚠️ You control all security layers
  • SOC 2 Type II – Independently audited
  • ISO certifications – 27001, 27018, 27701
  • HIPAA/GDPR/PCI DSS – Healthcare, privacy, payment compliance
  • FedRAMP – US government authorized
  • 6 data regions – US, EU, Singapore, India, Indonesia, UAE
  • SOC 2 Type II + GDPR – Regular third-party audits, full EU compliance
  • 256-bit AES encryption – Data at rest; SSL/TLS in transit
  • SSO + 2FA + RBAC – Enterprise access controls with role-based permissions
  • Data isolation – Never trains on customer data
  • Domain allowlisting – Restrict chatbot to approved domains
Pricing & Plans
  • MIT License – ✅ Free with no subscription or API charges
  • GPU Costs Only – Hardware or cloud compute are sole expenses
  • Unlimited Queries – No per-request pricing or rate limits
N/A
  • Standard: $99/mo – 10 chatbots, 60M words, 5K items/bot
  • Premium: $449/mo – 100 chatbots, 300M words, 20K items/bot
  • Enterprise: Custom – SSO, dedicated support, custom SLAs
  • 7-day free trial – Full Standard access, no charges
  • Flat-rate pricing – No per-query charges, no hidden costs
Support & Documentation
  • GitHub Repository – Code, docs, and examples at RCGAI/SimplyRetrieve
  • Academic Paper – arXiv 2308.03983 explaining RCG architecture
  • Community Support – GitHub Issues for troubleshooting
  • No Paid Support – ⚠️ Community-driven only, no SLAs
N/A
  • Documentation hub – Docs, tutorials, API references
  • Support channels – Email, in-app chat, dedicated managers (Premium+)
  • Open-source – Python SDK, Postman, GitHub examples
  • Community – User community + 5,000 Zapier integrations
Limitations & Considerations
  • Developer-Only Tool – ⚠️ Requires Python, GPU, and technical expertise
  • GPU Infrastructure Required – ⚠️ Dedicated hardware or cloud GPU needed
  • Basic UI – Gradio interface needs custom front-end for production
  • Manual Scaling – ⚠️ No auto-scaling, you manage load balancing
  • No Enterprise Features – Missing multi-tenancy, user management, analytics
  • Slower Inference – ⚠️ 3-10+ seconds vs sub-second cloud APIs
  • ⚠️ NOT RAG-as-a-Service – Embedded RAG, cannot use as knowledge backend
  • ⚠️ No API-first development – Cannot create bots or upload docs via API
  • ⚠️ Missing developer tools – No Python SDK, no npm package, no OpenAPI spec
  • ⚠️ No cloud storage – No Google Drive, Dropbox, Notion integration
  • ⚠️ High entry barrier – $10K-$25K annual, 4-month implementation
  • Best for – Enterprise omnichannel CX; poor fit for RAG API developers
  • Managed service – Less control over RAG pipeline vs build-your-own
  • Model selection – OpenAI + Anthropic only; no Cohere, AI21, open-source
  • Real-time data – Requires re-indexing; not ideal for live inventory/prices
  • Enterprise features – Custom SSO only on Enterprise plan
Core Agent Features
  • Retrieval-Centric Generation – Research approach separating reasoning from knowledge
  • Retrieval Tuning Module – ✅ Developer transparency showing document selection
  • Knowledge Base Mixing – Route queries across multiple sources
  • Single-Turn Focus – ⚠️ Limited multi-turn conversation memory
  • No Chatbot UI – ⚠️ Gradio for developers only
  • No Production Features – ⚠️ No lead capture, handoff, or multi-channel support
  • 16B+ conversations – Massive scale annually across enterprise deployments
  • 135+ languages – Including 11+ Indonesian variants (Komodo-7B)
  • Agentic RAG – Multi-checkpoint validation with guardrails
  • YellowG LLM – Claims <1% hallucination vs GPT-3's 22.7%
  • 0.6s response time – Optimized for conversational AI
  • Custom AI Agents – Autonomous GPT-4/Claude agents for business tasks
  • Multi-Agent Systems – Specialized agents for support, sales, knowledge
  • Memory & Context – Persistent conversation history across sessions
  • Tool Integration – Webhooks + 5,000 Zapier apps for automation
  • Continuous Learning – Auto re-indexing without manual retraining
R A G-as-a- Service Assessment
  • NOT RAG-AS-A-SERVICE – Open-source research project for local experimentation
  • Academic Foundation – Published research tool from RCGAI (arXiv 2308.03983)
  • Self-Hosted Only – ⚠️ No managed infrastructure, APIs, or SLAs
  • Developer-First Design – Python with GPU infrastructure requirements
  • 100% Local Execution – ✅ Perfect for air-gapped and classified environments
  • No Service Features – ⚠️ No auth, multi-tenancy, analytics, or SaaS conveniences
  • Platform type – Full-stack enterprise CX, NOT pure RAG-as-a-Service
  • Critical distinction – RAG embedded, not exposed as API
  • ⚠️ Cannot use as RAG backend – Queries must flow through platform
  • ⚠️ No RAG endpoints – No embedding access or vector store API
  • Comparison warning – vs CustomGPT is architecturally misleading
  • Platform type – TRUE RAG-AS-A-SERVICE with managed infrastructure
  • API-first – REST API, Python SDK, OpenAI compatibility, MCP Server
  • No-code option – 2-minute wizard deployment for non-developers
  • Hybrid positioning – Serves both dev teams (APIs) and business users (no-code)
  • Enterprise ready – SOC 2 Type II, GDPR, WCAG 2.0, flat-rate pricing
Competitive Positioning
  • Market Position – MIT open-source local RAG for on-premises deployment
  • Target Customers – Developers experimenting locally, strict data isolation orgs
  • Key Competitors – LangChain, LlamaIndex, PrivateGPT, LocalGPT
  • Advantages – ✅ Free MIT license, 100% local, full model control
  • Best For – Offline environments, GPU infrastructure teams, zero cloud costs
  • 35+ channel coverage – Unmatched omnichannel with WhatsApp BSP
  • Compliance leadership – SOC 2, ISO, HIPAA, GDPR, PCI DSS, FedRAMP
  • Gartner validated – Magic Quadrant Challenger status
  • ⚠️ Not RAG-as-a-Service – Embedded RAG, closed API
  • ⚠️ High entry barrier – $10K+ annual minimum
  • Market position – Leading RAG platform balancing enterprise accuracy with no-code usability. Trusted by 6,000+ orgs including Adobe, MIT, Dropbox.
  • Key differentiators – #1 benchmarked accuracy • 1,400+ formats • Full white-labeling included • Flat-rate pricing
  • vs OpenAI – 10% lower hallucination, 13% higher accuracy, 34% faster
  • vs Botsonic/Chatbase – More file formats, source citations, no hidden costs
  • vs LangChain – Production-ready in 2 min vs weeks of development
No- Code Interface & Usability
N/A
  • Visual Studio – Drag-and-drop flow builder
  • Dynamic AI Agent – Zero-training deployment
  • Pre-built templates – Industry-specific scenarios
  • ⚠️ Reality check – G2 reviews cite "steep learning curve"
  • ⚠️ Developer effort – Required for journey updates despite no-code claims
  • 2-minute deployment – Fastest time-to-value in the industry
  • Wizard interface – Step-by-step with visual previews
  • Drag-and-drop – Upload files, paste URLs, connect cloud storage
  • In-browser testing – Test before deploying to production
  • Zero learning curve – Productive on day one
Additional Considerations
N/A
  • Platform type – Enterprise CX platform with embedded RAG, NOT RaaS
  • ✅ 35+ channels – Exceptional omnichannel with 135+ languages
  • ✅ Compliance breadth – SOC 2, ISO, HIPAA, GDPR, PCI DSS, FedRAMP
  • ⚠️ Not for developers – No RAG API, Python SDK, or programmatic control
  • ⚠️ High entry barrier – $10K-$25K annual with 4-month implementation
  • Best for – Enterprises needing omnichannel CX automation at scale
  • Time-to-value – 2-minute deployment vs weeks with DIY
  • Always current – Auto-updates to latest GPT models
  • Proven scale – 6,000+ organizations, millions of queries
  • Multi-LLM – OpenAI + Claude reduces vendor lock-in

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Final Thoughts

Final Verdict: SimplyRetrieve vs Yellow.ai

After analyzing features, pricing, performance, and user feedback, both SimplyRetrieve and Yellow.ai 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 Yellow.ai

  • You value genuinely comprehensive 35+ channel coverage: whatsapp bsp, messenger, instagram, telegram, slack, teams, voice, sms
  • Exceptional compliance credentials: SOC 2, ISO 27001/27018/27701, HIPAA, GDPR, PCI DSS, FedRAMP
  • Multi-region data centers (US, EU, Singapore, India, Indonesia, UAE) with customer-selected residency

Best For: Genuinely comprehensive 35+ channel coverage: WhatsApp BSP, Messenger, Instagram, Telegram, Slack, Teams, voice, SMS

Migration & Switching Considerations

Switching between SimplyRetrieve and Yellow.ai 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 Yellow.ai 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

  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 Yellow.ai 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: February 23, 2026 | 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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