What are the main differences between RAGFlow and SearchUnify?

RAGFlow excels in Truly open-source (Apache 2.0) with 68K+ GitHub stars - vibrant community and State-of-the-art hybrid retrieval with multiple recall + fused re-ranking, scoring 80/100 in user ratings with N/A% accuracy. SearchUnify leads in G2 Leader for 21 consecutive quarters (5+ years) in Enterprise Search - exceptional market validation vs newer RAG startups and Proprietary FRAG™ architecture specifically designed for hallucination mitigation with 3-layer federation, retrieval, augmented generation with 84/100 overall rating and N/A% accuracy. Key technical difference: RAGFlow focuses on Deep document understanding with template-based chunking while SearchUnify emphasizes Federated RAG (FRAG™): Proprietary 3-layer architecture (Federation, Retrieval, Augmented Generation) for hallucination mitigation across 100+ enterprise sources.

Which is better for enterprises: RAGFlow or SearchUnify?

SearchUnify offers SOC 2 compliance for enterprise security. HIPAA compliance is available in SearchUnify. For scalability, both offer cloud-based deployment options. SearchUnify leads with 84/100 enterprise readiness score.

How much does RAGFlow cost vs SearchUnify?

RAGFlow starts at custom pricing/month (open-source model), while SearchUnify begins at contact sales/month (enterprise model). RAGFlow offers a free tier. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from RAGFlow to SearchUnify?

Migration from RAGFlow to SearchUnify typically requires API-based data export/import, which SearchUnify provides. SearchUnify provides comprehensive API access good documentation for the migration process. Estimated migration time: 1-2 weeks for full deployment. Contact SearchUnify support for migration assistance and best practices.

What integrations do RAGFlow and SearchUnify support?

RAGFlow integrates with RESTful APIs for conversation, query, and document management, Python interfaces for programmatic control, Reference chat demo UI included in repository, Developer-driven integrations (no pre-built channel connectors), Requires custom coding for Slack, Teams, WhatsApp, etc. (5 integrations total). SearchUnify supports Native search clients: Salesforce Service Console/Communities, ServiceNow, Zendesk Support/Help Center, Khoros Aurora/Classic, Slack, Marketplace presence: Salesforce AppExchange (Summit Partner), ServiceNow Store, Microsoft AppSource, Embedding: JavaScript widget, custom React/Handlebars components (Khoros), native widgets (Salesforce/ServiceNow consoles), SearchUnifyGPT™ Answer Box: LLM answers above traditional search with inline citations, Webhooks: Real-time sync and SUVA integration with external applications (8 integrations available). Both offer REST APIs for custom integrations. SearchUnify provides 60% more integrations.

What are the main differences between RAGFlow and SearchUnify?

RAGFlow offers strong capabilities, scoring 0/100 in user ratings. SearchUnify provides unique strengths with 0/100 overall rating. Key technical difference: RAGFlow focuses on advanced features while SearchUnify emphasizes specialized capabilities.

Which is better for enterprises: RAGFlow or SearchUnify?

Both platforms provide enterprise-grade security. HIPAA compliance varies - contact vendors for details. For scalability, both offer cloud-based deployment options. SearchUnify leads with strong/100 enterprise readiness score.

How much does RAGFlow cost vs SearchUnify?

RAGFlow starts at custom pricing/month (subscription model), while SearchUnify begins at contact sales/month (subscription model). Both require paid plans. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from RAGFlow to SearchUnify?

Migration from RAGFlow to SearchUnify typically requires manual data transfer since API access may be limited. SearchUnify offers standard documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact SearchUnify support for migration assistance and best practices.

What integrations do RAGFlow and SearchUnify support?

RAGFlow integrates with (multiple platforms). SearchUnify supports (various tools). API availability varies by plan. Integration coverage is comparable.

RAGFlow vs SearchUnify

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

More about SearchUnify More about RAGFlow Get Started Today

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 RAGFlow and SearchUnify 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 RAGFlow and SearchUnify, 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 RAGFlow if: you value truly open-source (apache 2.0) with 68k+ github stars - vibrant community
Choose SearchUnify if: you value g2 leader for 21 consecutive quarters (5+ years) in enterprise search - exceptional market validation vs newer rag startups

About RAGFlow

RAGFlow is open-source rag orchestration engine for document ai. Open-source RAG engine with deep document understanding, hybrid retrieval, and template-based chunking for extracting knowledge from complex formatted data. Founded in 2024, headquartered in Global (Open Source), the platform has established itself as a reliable solution in the RAG space.

Overall Rating

80/100

Starting Price

Custom

About SearchUnify

SearchUnify is ai-powered unified enterprise search and knowledge management. Enterprise cognitive search platform with proprietary Federated RAG (FRAG™) architecture, 100+ pre-built connectors, and mature Salesforce integration. G2 Leader for 21 consecutive quarters (5+ years). Parent company Grazitti Interactive (founded 2008) maintains SOC 2 Type 2 + ISO 27001 + HIPAA compliance. BYOLLM flexibility supports OpenAI, Azure, Google Gemini, Hugging Face, custom models. Critical gaps: NO WhatsApp/Telegram messaging, NO public pricing (AWS Marketplace: $0.01-$0.025/request), NO Zapier integration. Enterprise search heritage vs RAG-first positioning. Founded in 2008 (Grazitti), SearchUnify product launched ~2012, headquartered in Panchkula, India / San Jose, CA, USA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

84/100

Starting Price

Custom

Key Differences at a Glance

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

RAGFlow	SearchUnify	CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Deep document parsing – PDFs, Word, Excel, PowerPoint, images, scanned PDFs with OCR Layout recognition – Template-based chunking preserving structure, sections, headings External connectors – Confluence, AWS S3, Google Drive, Notion, Discord channels Scheduled sync – Automated refresh for continuous ingestion from external sources Elasticsearch backend – Handles unlimited tokens and millions of documents	35+ content parsers – PDF, DOC, DOCX, PPT, CSV, TXT, XSL with 12MB size limit per document 100+ pre-built connectors – Salesforce, ServiceNow, Zendesk, SharePoint, Confluence, Google Drive YouTube indexing – Channel/playlist/video-level with timestamped transcript search Auto-sync – 15-minute to manual intervals, webhook-based real-time for Box, Docebo ⚠️ No Notion integration – Notable gap vs competitors supporting Notion knowledge bases ⚠️ 12MB document limit – May constrain large PDF processing	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
⚠️ No native integrations – No pre-built Slack, Teams, WhatsApp, Telegram API-driven – RESTful conversation/query APIs for custom integrations Reference chat UI – Demo interface included, can be embedded or customized Ultimate flexibility – Integrate with any platform via API with engineering work	Native search clients – Salesforce Service Console, ServiceNow, Zendesk, Khoros, Slack Salesforce Summit Partner – Highest tier with AppExchange, native UX integration RESTful API – OAuth 2.0, Swagger docs, three official SDKs (JS, Python, Java) ⚠️ No consumer messaging – NO WhatsApp, Telegram, Facebook Messenger ⚠️ No Zapier – Significant gap for no-code automation vs 7,000+ app competitors	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
Advanced R A G ( Core Differentiator)
GraphRAG – Graph-based retrieval for relationship-aware knowledge extraction RAPTOR – Recursive abstractive processing for tree-organized retrieval Agentic workflows – Multi-step reasoning, tool use, code execution in sandbox Hybrid search – Full-text + vector + ML re-ranking combined ✅ 68K+ GitHub stars – Fastest-growing open-source RAG project (Octoverse 2024)	N/A	N/A
Core Agent Features
Multi-turn context – Session-based conversation API (v0.22+) Grounded citations – Answers backed by source text chunks Multi-lingual – Depends on chosen LLM, Chinese UI native ⚠️ No lead capture – Requires custom frontend implementation ⚠️ No analytics dashboard – Must integrate external tools	SUVA Virtual Assistant – "World's First Federated RAG Chatbot" analyzing 20+ attributes 35+ languages – Native Arabic, German, French, Mandarin with extended CSV config Human handoff – Escalation to Salesforce, Zendesk, Khoros with full context SearchUnifyGPT™ – LLM answers with inline citations above traditional search Up to 5 agents – Per instance deployable across portals	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
L L M Model Options
Model agnostic – OpenAI GPT-4/3.5, Claude 3, Gemini, Llama, Mistral Local deployment – Ollama, Xinference, IPEX-LLM for complete offline Chinese LLMs – Baichuan, Tencent Hunyuan, Baidu Yiyan, XunFei Spark OpenAI-compatible – Any model with compatible API endpoints ✅ No vendor lock-in – Swap providers freely	BYOLLM architecture – Avoid vendor lock-in with flexible model selection Claude via Bedrock – 14-day trial, OpenAI, Azure OpenAI, Google Gemini Hugging Face support – Open-source models for custom deployments Multiple connections – Connect providers simultaneously with failover ⚠️ No auto routing – Manual configuration vs query complexity-based routing	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)
RESTful APIs – Document upload, parsing, datasets, conversation queries Python interfaces – Library calls for programmatic control Extensive docs – ragflow.io/docs with guides and examples ⚠️ No packaged SDK – HTTP requests or direct module calls ⚠️ Docker required – Self-hosted setup with technical expertise	Three official SDKs – JavaScript (su-sdk), Python (searchunify), Java (Maven) MCP support – su-mcp library for Claude Desktop and LLM tooling RESTful API v2 – Swagger docs, OAuth 2.0 (4-hour access, 14-day refresh tokens) ⚠️ Rate limits unclear – Requires community documentation access ⚠️ No API versioning policy – Potential breaking change risk	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
Hybrid retrieval – Full-text + vector + multiple recall with fused re-ranking Grounded citations – Reduces hallucinations with source transparency Deep document parsing – Layout recognition improves retrieval precision Production-grade – Elasticsearch-backed for large datasets and fast queries ✅ Community validated – 68K+ stars, many production deployments	120-second analytics – Near real-time dashboard refresh FRAG™ mitigation – 3-layer architecture reduces hallucinations Customer results – Accela 99.7% cost savings, Cornerstone 98% self-service YouTube timestamps – Transcript search returns exact audio segments	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
Security & Compliance
Complete data control – Self-hosted, data never leaves your infrastructure On-premise deployment – Suitable for government/corporate secrets Air-gapped option – Local LLMs eliminate external API exposure User-configured encryption – TLS, VPN, OS-level disk encryption ⚠️ No formal certifications – SOC 2, ISO 27001 via deployment config	SOC 1/2/3 Type II – ISO 27001, ISO 27701, HIPAA, GDPR compliant Single-tenant – Customer data isolation, no cross-tenant leakage AES-256 + TLS 1.3 – Encryption at rest and in transit SSO integration – SAML 2.0 with Okta, Azure AD, OneLogin, Google FRAG security – Sensitive data removal before LLM transmission	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
License: $0 – Apache 2.0 open-source, free to use and modify Infrastructure costs – Cloud VMs, storage, networking paid by user LLM API costs – Separate charges for OpenAI/Anthropic (eliminable with local) Engineering costs – DevOps for installation, maintenance, updates ⚠️ TCO variability – Can exceed SaaS for smaller deployments	⚠️ No public pricing – Requires enterprise sales engagement AWS Marketplace – 100K searches: $0.025/req, 200K: $0.015, 300K: $0.01 Unlimited connectors – Flat subscription, no per-connector fees 7-14 day deployment – Using pre-built connectors ⚠️ Annual escalation – Reviews note "guaranteed price increase every year"	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
Customization & Branding
Full source access – Modify Admin UI, styling, behavior at code level White-labeling – Complete branding removal via code editing Custom frontend – Build entirely custom chat using RAGFlow as backend ⚠️ No point-and-click – UI changes require config/code editing	Theme editor – Colors, fonts, icons, messaging without code NLP Manager – Synonyms, acronyms, keywords per language Visual search tuning – Boost/downgrade rankings via admin UI Temperature controls – Per-persona, use case, audience type	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
Observability & Monitoring
⚠️ No built-in analytics – Basic admin stats only (doc counts, query history) Logs – Console and file logs for operations and errors External integration – Prometheus, Grafana, Datadog, Splunk compatible Ultimate flexibility – Instrument with any monitoring stack	30+ pre-built metrics – Search performance, conversion tracking, content gaps Actionable Insights – AI-generated plain-English recommendations SUVA metrics – Deflection rate, handover, CSAT, LLM token usage Admin activity logs – 30-day retention with CSV export	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
68K+ GitHub stars – Largest open-source RAG community Active Discord – Real-time help from users and maintainers Rapid releases – Modern features often before commercial platforms ⚠️ No SLA – Community support, no guaranteed response times	SearchUnify Academy – Free training with certifications 97-98% G2 satisfaction – "Ease of Doing Business With" rating G2 Leader – 21 consecutive quarters in Enterprise Search Enterprise support – Phone, email, chat with dedicated account managers	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
R A G-as-a- Service Assessment
Platform type – TRUE RAG PLATFORM (Open-Source Engine), NOT SaaS Hybrid retrieval – Full-text + vector + re-ranking with deep document parsing Model agnostic – Any LLM (OpenAI, local, custom) without vendor lock-in Target users – Developer teams, enterprises with DevOps capabilities ⚠️ Not for non-technical – Requires Docker, infrastructure management	Platform type – ENTERPRISE COGNITIVE SEARCH with RAG, not pure RaaS 5+ years leadership – G2 Leader 21 quarters with RAG as enhancement FRAG™ differentiator – Proprietary federated architecture for enterprise Target users – Large enterprises with 100+ fragmented knowledge sources ⚠️ Not for developers – Not lightweight API-first RAG for SMBs	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
Open-source freedom – Zero licensing costs, complete customization Technical superiority – Hybrid retrieval often exceeds commercial accuracy Data sovereignty – Self-hosted ensures complete data control Innovation speed – GraphRAG, agentic workflows before many commercial platforms ⚠️ DevOps required – Not for teams without technical resources	G2 + IDC + Forrester – Leader 21 quarters, MarketScape Major Player 100+ connectors – Reduced integration effort vs custom connector platforms Salesforce Summit – Native UX integration vs API-only competitors ⚠️ Cloud-only – No on-premise/air-gapped deployment ⚠️ No consumer messaging – Enterprise support channels only	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
A I Models
OpenAI – GPT-4, GPT-4o, GPT-4o-mini, GPT-3.5-turbo and all compatible Anthropic – Claude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku Google – Gemini Pro and Gemini Ultra via Cloud integration Local models – Ollama, Xinference, IPEX-LLM for complete offline Open-source – Llama 2/3, Mistral, DeepSeek, WizardLM, Vicuna	BYOLLM – Claude (Bedrock), OpenAI, Azure, Gemini, Hugging Face Multiple connections – Simultaneous providers with activation toggles Temperature controls – Per-persona creativity adjustment Failover mechanisms – Automatic when primary LLMs unavailable	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
Hybrid retrieval – Full-text + vector + multiple recall with fused re-ranking GraphRAG – Relationship-aware knowledge extraction across entities RAPTOR – Hierarchical tree-organized retrieval structures Template-based chunking – Document-type-specific strategies preserving structure Code sandbox – Safe execution for complex analytical tasks	FRAG™ 3-layer – Federation + Retrieval + Augmented Generation Hybrid search – Full-text + vector + ML re-ranking combined Multi-repository – Docs, forums, LMS, CRM unified retrieval Hallucination mitigation – Sensitive data removal before LLM transmission	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
Enterprise document analysis – Financial risk, fraud detection, investment research Legal document processing – Structure preservation, citation tracking Healthcare – Clinical decision support with strict data privacy Government/defense – Classified analysis with air-gapped deployment Research & development – Scientific papers, patents, literature review	Enterprise support – SUVA deflects tickets with federated knowledge Salesforce enhancement – Native Service Console and Communities integration Multi-system unification – 100+ sources consolidated (CRM, LMS, SharePoint) Training/LMS search – YouTube transcripts + Docebo + documentation unified	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
No- Code Interface & Usability
Admin UI (v0.22+) – Basic file upload, dataset management, connections ⚠️ Not true no-code – Docker, OAuth config requires technical setup Power user access – Analysts can maintain after developer setup ⚠️ Single admin login – No RBAC by default, requires custom implementation	97-98% G2 usability – Consistently high "Ease of Use" ratings Visual configuration – OAuth flows, content sources via admin UI Drag-and-drop – Salesforce Console search client components SUVA Agent Builder – Visual config for up to 5 agents per instance	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
✅ Open-source freedom – Zero licensing, complete customization ✅ Modern RAG features – GraphRAG, RAPTOR, agentic workflows ✅ Data sovereignty – Self-hosted, air-gapped operation possible ⚠️ DevOps expertise required – Docker, infrastructure management ⚠️ Maintenance burden – Updates, patches, monitoring, backups on user ⚠️ No commercial SLA – Community support only	✅ 100+ connectors – Reduced integration effort, 7-14 day deployment ✅ FRAG™ architecture – Enterprise hallucination mitigation ✅ Salesforce Summit – Deepest native integration available ⚠️ Cloud-only – No on-premise/air-gapped option ⚠️ No public pricing – Requires sales engagement ⚠️ No consumer messaging – WhatsApp, Telegram, Zapier absent	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
Limitations & Considerations
⚠️ DevOps expertise required – Not for teams without container orchestration skills ⚠️ No managed service – Self-hosted only, no SaaS option available ⚠️ Maintenance burden – Docker updates, security patches, monitoring on user ⚠️ No native channel integrations – API-driven custom development required ⚠️ No built-in analytics – External tools (Prometheus, Grafana) required Best for – Enterprises with DevOps; poor fit for rapid deployment needs	⚠️ No public pricing – Requires sales engagement, annual escalation clauses ⚠️ No consumer messaging – NO WhatsApp, Telegram, Messenger native ⚠️ No Zapier – Major gap for no-code automation workflows ⚠️ Cloud-only – No on-premise/air-gapped for regulated industries ⚠️ 12MB document limit – May constrain large PDF processing Best for – Salesforce-centric enterprises; not API-first 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
F R A G™ Architecture ( Core Differentiator)
N/A	Federated RAG – 3-layer framework for hallucination mitigation in enterprise retrieval Federation Layer – 360-degree context across 100+ connected sources simultaneously Retrieval Layer – Keyword matching + semantic similarity + vector search combined ✅ Multi-repository context – Docs, forums, LMS, CRM, tickets unified for comprehensive answers	N/A
Core Chatbot Features
N/A	N/A	✅ #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)
N/A	N/A	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
N/A	N/A	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
N/A	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
Support & Documentation
N/A	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

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Final Thoughts

Final Verdict: RAGFlow vs SearchUnify

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

When to Choose RAGFlow

You value truly open-source (apache 2.0) with 68k+ github stars - vibrant community
State-of-the-art hybrid retrieval with multiple recall + fused re-ranking
Deep document understanding extracts knowledge from complex formats (OCR, layouts)

Best For: Truly open-source (Apache 2.0) with 68K+ GitHub stars - vibrant community

When to Choose SearchUnify

You value g2 leader for 21 consecutive quarters (5+ years) in enterprise search - exceptional market validation vs newer rag startups
Proprietary FRAG™ architecture specifically designed for hallucination mitigation with 3-layer federation, retrieval, augmented generation
100+ pre-built connectors dramatically reduce integration effort - Google Drive, Salesforce, ServiceNow, Zendesk, Slack, MS Teams, YouTube, Adobe AEM

Best For: G2 Leader for 21 consecutive quarters (5+ years) in Enterprise Search - exceptional market validation vs newer RAG startups

Migration & Switching Considerations

Switching between RAGFlow and SearchUnify 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

RAGFlow starts at custom pricing, while SearchUnify 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 RAGFlow and SearchUnify 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

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.

RAGFlow vs SearchUnify