Denser.ai vs SimplyRetrieve

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 Denser.ai 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 Denser.ai 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 Denser.ai if: you value state-of-the-art hybrid retrieval (75.33 ndcg@10) outperforms pure vector search with published benchmarks
  • Choose SimplyRetrieve if: you value completely free and open source

About Denser.ai

Denser.ai Landing Page Screenshot

Denser.ai is open-source hybrid rag with state-of-the-art retrieval architecture. Denser.ai is a developer-focused RAG platform built by former Amazon Kendra principal scientist Zhiheng Huang, combining open-source retrieval technology with no-code deployment. Its hybrid architecture fuses Elasticsearch, Milvus vector search, and XGBoost ML reranking to achieve 75.33 NDCG@10 (vs 73.16 for pure vector search) and 96.50% Recall@20 on benchmarks. Trade-offs: no SOC2/HIPAA certifications, limited native integrations, ~4-person team size impacts enterprise support. Founded in 2023, headquartered in Silicon Valley, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
88/100
Starting Price
$19/mo

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

Key Differences at a Glance

In terms of user ratings, Denser.ai in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: RAG Platform versus RAG Platform. These differences make each platform better suited for specific use cases and organizational requirements.

⚠️ What This Comparison Covers

We'll analyze features, pricing, performance benchmarks, security compliance, integration capabilities, and real-world use cases to help you determine which platform best fits your organization's needs. All data is independently verified from official documentation and third-party review platforms.

Detailed Feature Comparison

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Denser.ai
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SimplyRetrieve
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Data Ingestion & Knowledge Sources
  • Document formats – PDF, DOCX, PPTX, CSV, TXT, HTML; 5MB free tier limit
  • Website crawling – Hundreds of thousands of pages indexed under 5 minutes
  • Google Drive – Native integration with real-time sync for cloud content
  • SQL databases – MySQL, PostgreSQL, Oracle, SQL Server, AWS/Azure/Google Cloud SQL
  • ⚠️ YouTube, Dropbox, Notion, OneDrive – Zapier middleware required (no native integration)
  • 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
  • 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
Hybrid Retrieval Architecture ( Core Differentiator)
  • ✅ Three-component system – Elasticsearch + Milvus vectors + XGBoost ML reranking
  • 75.33 NDCG@10 – MTEB vs 73.16 pure vector (3% improvement)
  • 96.50% Recall@20 – Anthropic benchmark vs 90.06% baseline
  • Models – snowflake-arctic-embed-m, bge-en-icl, voyage-2, OpenAI text-embedding-3-large
  • ✅ Key finding – Open-source models match/exceed paid alternatives in benchmarks
N/A
N/A
Performance & Accuracy
  • 98.3% response accuracy – Claimed with 1.2-second average response
  • Source citation – Visual PDF highlighting with page-level references
  • ⚠️ No published uptime SLA – Service reliability not documented
  • 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
  • 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
Developer Experience ( A P I & S D Ks)
  • REST API + GraphQL – Bearer token auth with scored passage responses
  • denser-retriever – MIT-licensed Python package (261 stars, 30 forks)
  • Docker Compose – Full stack with Elasticsearch and Milvus containers
  • ⚠️ Self-hosted "not production suitable" – Requires additional persistence and secrets config
  • Rate limits – 200 API calls/month on free tier
  • 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
  • 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
L L M Model Options
  • Supported LLMs – GPT-4o, GPT-4o mini, GPT-3.5, Claude (version unspecified)
  • API keys – Users provide OpenAI or Claude keys via environment
  • ⚠️ No custom fine-tuning – No private model hosting documented
  • 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
  • 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
Integrations & Channels
  • Website deployment – JavaScript widget (single line), iFrame, REST API
  • WordPress – Official plugin with page-specific targeting for no-code install
  • Zapier – 6,000+ apps with lead form triggers and events
  • ⚠️ No native Slack, Teams, Discord – WhatsApp via Zapier only
  • ⚠️ CRM via Zapier only – HubSpot, Salesforce, Zendesk not native
  • 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
  • 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
Customization & Branding
  • Drag-and-drop builder – Theme colors, logos, button sizing, bubbles
  • Custom domains – Available on paid tiers for white-labeling
  • Welcome messages – Configure suggested questions and greetings
  • Plain Gradio Interface – Minimal theming with developer-focused design
  • Source Code Customization – Tweak code or build custom front-end for branding
  • 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
No- Code Interface & Usability
  • Visual builder – Drag-and-drop theme customization without coding
  • Setup – Single line JavaScript; WordPress plugin for no-code
  • ⚠️ Learning curve – Documentation fragmented across multiple sites
  • ⚠️ ~4-person team – Impacts enterprise support capacity
N/A
  • 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
Lead Capture & Marketing
  • Integrated lead capture – Configurable fields (name, email, company, role, phone)
  • Conversation-triggered forms – Dynamic deployment based on conversation context
  • Analytics dashboard – Lead quality, satisfaction scores, conversion trends
  • ✅ 24.8% conversion rate – Claimed on homepage demonstrating effectiveness
N/A
N/A
Multi- Language & Localization
  • 80+ languages – Automatic language detection for global deployments
  • Multilingual rerankers – jinaai/jina-reranker-v2-base-multilingual support
N/A
N/A
Conversation Management
  • Conversation history – 30-360 days retention by tier
  • Human handoff – Triggers when complexity exceeds scope
  • Escalation workflows – Zendesk ticket creation for handoffs
N/A
N/A
Observability & Monitoring
  • Conversation logs – Retention by tier (30-360 days)
  • User engagement tracking – Common queries, conversation length, drop-off points
  • ⚠️ No A/B testing – No third-party BI integration (Tableau, PowerBI)
  • ⚠️ No real-time alerting – No documented SLA tracking
  • Analysis Tab – Shows retrieved docs and query construction process
  • Console Logging – Basic logs printed to terminal
  • No Dashboard – ⚠️ Add your own monitoring for stats
  • 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
S Q L Database Chat ( Unique Feature)
  • ✅ Direct SQL connectivity – Conversational BI across major databases
  • Supported databases – MySQL, PostgreSQL, Oracle, SQL Server, AWS/Azure/Google Cloud SQL
  • Natural language to SQL – Ask questions, receive database query results
  • AES-256 encryption – Secure connections with read-only access requirement
N/A
N/A
Pricing & Scalability
  • Free – $0: 1 chatbot, 20 queries/month, 5MB limit
  • Starter – $19-29/month: 2 chatbots, 1,500 queries/month, 30-day logs
  • Standard – $89-119/month: 4 chatbots, 7,500 queries/month, custom domain
  • Business – $399-799/month: 8 chatbots, 15,000 queries/month, priority support
  • Enterprise – Custom: Private cloud, dedicated support, AWS Marketplace
  • ⚠️ User feedback – "Plans quite restrictive, credit limits reached sooner"
  • 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
  • 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
  • ⚠️ NO SOC 2, HIPAA, ISO 27001, GDPR certifications – Not for regulated industries
  • Private cloud deployments – Enterprise tier for data sovereignty
  • AES-256 encryption – Database connections with read-only access
  • AWS infrastructure – Data storage and processing on AWS
  • 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
  • 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
Open- Source Components
  • ✅ denser-retriever – MIT-licensed, 261 GitHub stars, full RAG transparency
  • Docker Compose deployment – Local experimentation with Elasticsearch and Milvus
  • Validate benchmarks – Test embeddings, rerankers, chunking on own data
  • ⚠️ Self-hosted "not production suitable" – Denser recommends managed SaaS
N/A
N/A
Company Background
  • Founded 2023 – Silicon Valley startup, ~4 employees (bootstrapped)
  • ✅ Founder Zhiheng Huang – Former Amazon Kendra scientist, Amazon Q lead
  • 70+ research papers – 14,000+ citations; BLSTM-CRF 5,400+ citations
N/A
N/A
R A G-as-a- Service Assessment
  • ✅ TRUE RAG PLATFORM – Hybrid retrieval with open-source transparency
  • Data source flexibility – Good (documents, websites, Google Drive, SQL)
  • LLM model options – Good (GPT-4o, Claude, multiple embeddings/rerankers)
  • ✅ Open-source transparency – Excellent (MIT-licensed core, published benchmarks)
  • ⚠️ Compliance & certifications – Poor (no SOC 2, HIPAA, ISO 27001)
  • Best for – Technical teams prioritizing retrieval accuracy and validation
  • 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 – 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
  • vs CustomGPT – Superior retrieval transparency, SQL chat; gaps in compliance
  • vs Glean – Open-source vs proprietary, lower cost; lacks permissions-aware AI
  • ✅ Unique strengths – Hybrid retrieval benchmarks, founder pedigree, SQL chat
  • Target audience – Developers building AI chatbots without strict compliance
  • 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
  • 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
R A G Capabilities
  • ✅ Hybrid retrieval – ES + Milvus vectors + XGBoost reranking
  • 75.33 NDCG@10 on MTEB – vs 73.16 pure vector (3% improvement)
  • 96.50% Recall@20 – Anthropic benchmark vs 90.06% baseline
  • Source citation – Visual PDF highlighting with page references
  • 98.3% accuracy claimed – 1.2-second average response time
  • 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
  • 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
  • Customer support chatbots – Website deployment with 24.8% conversion rate
  • ✅ SQL database chat (unique) – Natural language queries against major databases
  • Technical documentation – Hundreds of thousands of pages indexed under 5 minutes
  • Multilingual support – 80+ languages with automatic detection
  • Developer-focused RAG – MIT-licensed denser-retriever for validation
  • 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 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
Support & Documentation
  • Documentation – docs.denser.ai, retriever.denser.ai, GitHub READMEs
  • ⚠️ Documentation fragmented – Information scattered across multiple sites
  • ~4-person team – Impacts enterprise support capacity
  • Open-source community – 261 GitHub stars, 30 forks, MIT license
  • 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
  • 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
  • ⚠️ No compliance certifications – Missing SOC 2, HIPAA, ISO 27001, GDPR
  • ⚠️ Small team (~4 people) – Potential scaling constraints for enterprise
  • ⚠️ Heavy Zapier dependency – No native Slack, Teams, CRM integrations
  • ⚠️ Fragmented documentation – Scattered across docs, retriever docs, GitHub
  • ⚠️ User feedback – "Plans restrictive, credit limits reached sooner"
  • 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
  • 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
  • AI agent capabilities – Process data for intelligent automation with customization
  • Multi-platform deployment – Launch across websites and messaging with single line
  • Adaptive learning – Chatbot learns over time using conversation analysis
  • 24/7 availability – Smart AI support with instant answers
  • 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
  • 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
Core Chatbot Features
  • Conversational interface – Chat with customers in friendly manner
  • Business knowledge integration – Trained on documents, websites, Google Drive
  • Multi-language support – 80+ languages with automatic detection
  • Lead capture – Integrated forms (name, email, company, role)
  • Human handoff – Triggers on complexity with Zendesk tickets
  • 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
  • ✅ #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 & Flexibility ( Behavior & Knowledge)
  • Behavior customization – Define name, tone, response preferences
  • File support – PDF, DOCX, XLSX, PPTX, TXT, HTML, CSV, XML
  • Website crawling – Train bot by crawling URLs for knowledge base
  • Easy knowledge updates – Add documents, re-crawl, update without rebuild
  • Flexible deployment – Web widget, dashboard, or API integration
  • 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
  • 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
Support & Ecosystem
N/A
  • 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
  • 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
N/A
  • 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
  • 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
Security & Compliance
N/A
  • 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 + 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
N/A
  • 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
  • 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
Additional Considerations
N/A
N/A
  • 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: Denser.ai vs SimplyRetrieve

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

When to Choose Denser.ai

  • You value state-of-the-art hybrid retrieval (75.33 ndcg@10) outperforms pure vector search with published benchmarks
  • Open-source MIT-licensed core (denser-retriever) enables transparency, validation, and self-hosting
  • SQL database chat capability unique differentiator for business intelligence use cases

Best For: State-of-the-art hybrid retrieval (75.33 NDCG@10) outperforms pure vector search with published benchmarks

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 Denser.ai 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

Denser.ai starts at $19/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

  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 Denser.ai 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: February 23, 2026 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

See Also

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The most accurate RAG-as-a-Service API. Deliver production-ready reliable RAG applications faster. Benchmarked #1 in accuracy and hallucinations for fully managed RAG-as-a-Service API.

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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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