Which is better for enterprises: Progress Agentic RAG or RAGFlow?

Progress Agentic RAG offers SOC 2 compliance for enterprise security. HIPAA compliance varies - contact vendors for details. For scalability, both offer cloud-based deployment options. Progress Agentic RAG leads with 82/100 enterprise readiness score.

How much does Progress Agentic RAG cost vs RAGFlow?

Progress Agentic RAG starts at $700/monthly (paid model), while RAGFlow begins at contact sales/month (open-source model). RAGFlow provides a free tier. This represents a significant price difference of $700/month. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from RAGFlow to Progress Agentic RAG?

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

What integrations do Progress Agentic RAG and RAGFlow support?

Progress Agentic RAG integrates with Python SDK: pip install nuclia (Python 3.8+, ~21K weekly downloads), JavaScript/TypeScript SDK: @nuclia/core (React, Next.js, Angular, Vue.js, Svelte), CMS plugins: WordPress, Strapi, Workflow: Pipedream official app, Zapier API-compatible, Chrome extension for web page indexing (7 integrations total). RAGFlow supports 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 available). Both offer REST APIs for custom integrations. Progress Agentic RAG offers 40% more integrations.

What are the main differences between Progress Agentic RAG and RAGFlow?

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

Which is better for enterprises: Progress Agentic RAG or RAGFlow?

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

How much does Progress Agentic RAG cost vs RAGFlow?

Progress Agentic RAG starts at custom pricing/month (subscription model), while RAGFlow 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 Progress Agentic RAG to RAGFlow?

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

What integrations do Progress Agentic RAG and RAGFlow support?

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

Progress Agentic RAG vs RAGFlow

Q: What are the main differences between Progress Agentic RAG and RAGFlow?

Progress Agentic RAG excels in Proprietary REMi v2 model (30x faster inference) addresses hallucination problem with continuous quality monitoring - differentiated capability absent from most competitors and Open-source NucliaDB transparency (710+ GitHub stars) with managed infrastructure removes operational burden while maintaining technical visibility, scoring 82/100 in user ratings with N/A% accuracy. RAGFlow leads 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 with 80/100 overall rating and N/A% accuracy. Key technical difference: Progress Agentic RAG focuses on REMi evaluation model v2 (Llama 3.2-3B) for continuous quality scoring: answer relevance, context relevance, groundedness, correctness (0-5 scale) while RAGFlow emphasizes Deep document understanding with template-based chunking. Pricing differs by $700/month.

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

More about RAGFlow More about Progress Agentic RAG 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 Progress Agentic RAG and RAGFlow 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 Progress Agentic RAG and RAGFlow, 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 Progress Agentic RAG if: you value proprietary remi v2 model (30x faster inference) addresses hallucination problem with continuous quality monitoring - differentiated capability absent from most competitors
Choose RAGFlow if: you value truly open-source (apache 2.0) with 68k+ github stars - vibrant community

About Progress Agentic RAG

Progress Agentic RAG Landing Page Screenshot

Progress Agentic RAG is enterprise application development and deployment platform. Enterprise RAG-as-a-Service platform launched Sept 2025 following Progress Software's acquisition of Barcelona-based Nuclia. Combines SOC2/ISO 27001 security with proprietary REMi evaluation model for continuous answer quality monitoring. Built on open-source NucliaDB (710+ GitHub stars) with Python/JavaScript SDKs. Starting at $700/month. Founded in 2019 (Nuclia), acquired 2025, headquartered in Barcelona, Spain (Nuclia) / Bedford, MA, USA (Progress), the platform has established itself as a reliable solution in the RAG space.

Overall Rating

82/100

Starting Price

$700/mo

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

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, RAGFlow offers more competitive entry pricing. The platforms also differ in their primary focus: Enterprise Software 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

Progress Agentic RAG	RAGFlow	CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
60+ Document Formats – PDF, Word, Excel, PPT, email with auto parsing Multimedia Processing – Auto speech-to-text, video transcripts, OCR for scans Cloud Connectors – SharePoint, Confluence, OneDrive, Google Drive, S3 Fast Deployment – 2-hour initial ingestion, 48-hour full deployment ⚠️ Missing – No Dropbox, Notion, or YouTube transcript integration	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	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
Python SDK – 21K weekly downloads, Python 3.8+ support JavaScript/TypeScript SDK – React, Next.js, Angular, Vue, Svelte support Progress Ecosystem – OpenEdge database, Sitefinity CMS integration ⚠️ No Messaging Channels – No native Slack, WhatsApp, Teams integrations	⚠️ 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	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
AI Search & Answers – Semantic search with source-linked trusted answers Multi-Turn Conversations – Context-aware dialogue maintains conversation history Multilingual Support – Nuclia multilingual embedding model handles multiple languages ⚠️ Missing – No lead capture or human handoff workflows	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
Core Agent Features
Retrieval Agents – Autonomously select optimal retrieval strategies per query Pre-Built Agents (Beta) – Labeler, summarization, graph extraction, Q&A, safety Web Components – <nuclia-search-bar> and <nuclia-chat> for embedding ⚠️ No Proactive Alerts – Monitoring exists but alerting undocumented	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	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
Additional Considerations
✅ REMi Quality – 30x faster v2, continuous evaluation addresses hallucination ✅ Open-Source Trust – NucliaDB 710+ stars enables security audits ⚠️ Recent Acquisition – June 2025 Progress purchase, platform transitioning	✅ 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	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
Customization & Branding
Prompt Lab – Test LLMs side-by-side using actual customer data 30+ RAG Parameters – Custom chunking, context size, hybrid search weighting Widget Customization – Visual editor for filters, metadata, thumbnails, answer modes RBAC – Account and Knowledge Box level permissions with SSO	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	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
7 Providers – Anthropic, OpenAI, Google, Meta Llama, Mistral, Cohere Nuclia Private GenAI – 100% data isolation for maximum security Model Switching – Change providers without architectural changes	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	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)
Open-Source Foundation – NucliaDB 710+ stars, AGPLv3, Python/Rust Python SDK – 21K weekly downloads, full API coverage JavaScript/TypeScript SDK – React, Next.js, Angular, Vue, Svelte support REST API – Regional endpoints /ask, /find, /upload, /remi	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	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
✅ Benchmark Leader – Highest scores vs Vectara on Docmatix 1.4k dataset 100M Vectors – Fully ingested and optimized in ~20 minutes REMi v2 Speed – 30x faster inference, Llama 3.2-3B based Four-Index Hybrid – Document, Full Text, Vector/Chunk, Knowledge Graph	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	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)
30+ RAG Parameters – Fine-grained control over retrieval behavior Hybrid Weighting – Balance keyword vs semantic search relevance Agent Autonomy – Auto select optimal strategies per query Prompt Lab – Test configurations with actual data before production	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
Fly – $700/mo: 10GB/15K resources, 750MB max file Growth – $1,750/mo: 50GB/80K resources, 1.5GB max, Prompt Lab Enterprise – Custom: Unlimited data, 11 KBs, hybrid/on-prem ✅ Competitive Entry – $700/mo undercuts enterprise alternatives	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
✅ SOC2 Type 2 – Annually audited enterprise security ✅ ISO 27001 – Annually audited information security management ✅ GDPR Compliant – Built-in PII anonymization auto-detects personal data Encryption – AES-256 at rest, TLS in transit ⚠️ NO HIPAA – Healthcare PHI processing requires sales clarification	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
REMi Dashboard – Real-time metrics for relevance, groundedness, correctness (0-5) Rolling Averages – Performance graphs spanning 24h to 30 days Benchmark Validated – Tested vs Vectara on Docmatix 1.4k dataset ⚠️ No Proactive Alerts – Alerting not documented despite 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	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
Documentation – docs.rag.progress.cloud + legacy docs.nuclia.dev SDK Ecosystem – Python 21K weekly + JavaScript/TypeScript active usage Progress Support – 2,000+ employee parent company infrastructure AWS Marketplace – November 2025 for streamlined procurement	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	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
No- Code Interface & Usability
Target Users – Non-technical teams: marketing, HR, legal, support Visual Dashboard – Create KB, upload docs, deploy widget in one session Point-and-Click Editor – Configure suggestions, filters, metadata visually Rapid Deployment – Minutes-to-production capability for business users	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	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
R E Mi Evaluation Model ( Core Differentiator)
✅ Proprietary Investment – Addresses hallucination, absent from competitors REMi v2 – Llama 3.2-3B based, 30x faster inference Continuous Quality – Evaluates every interaction across 4 dimensions (0-5) ✅ Benchmark Leader – Highest scores vs Vectara on Docmatix 1.4k	N/A	N/A
Open- Source Nuclia D B Foundation
GitHub Presence – 710+ stars, AGPLv3 transparency into retrieval Technology Stack – Python and Rust for performance Four Index Types – Document, Full Text, Chunk/Vector, Knowledge Graph 100M Vector Performance – Full ingestion in ~20 minutes	N/A	N/A
Multi- Lingual Support
Nuclia Multilingual Embedding – Default model supports multiple languages 60+ Format Processing – Multi-language across PDF, Word, Excel, PPT Auto Transcription – Multi-language speech-to-text for audio/video	N/A	N/A
R A G-as-a- Service Assessment
✅ TRUE RAG-AS-A-SERVICE – Core mission is RAG backend LLM Flexibility – 7 providers switchable without changes Open-Source – NucliaDB 710+ stars, AGPLv3	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 – 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
✅ Pricing Advantage – $700/mo entry undercuts competitors ✅ REMi Differentiator – Continuous quality monitoring ⚠️ Integration Gaps – No native Slack/WhatsApp/Teams	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	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
7 Providers – Anthropic, OpenAI, Google, Meta, Mistral, Cohere Nuclia Private GenAI – 100% data isolation for security	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	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
Agentic RAG Engine – Retrieval agents auto-select strategies Four-Index Hybrid – Document, Full Text, Vector, Knowledge Graph REMi v2 Quality – Continuous evaluation, 30x faster Multimodal – OCR, speech-to-text, 60+ formats	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	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 Knowledge – Deploy knowledge bases in minutes Healthcare & Pharma – Medical protocol search Developer RAG Backend – API-first for custom AI apps	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	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
✅ SOC2 Type 2, ISO 27001, GDPR Encryption – AES-256 at rest, TLS in transit ⚠️ NO HIPAA – Healthcare requires sales contact	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 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
Fly – $700/mo: 10GB/15K resources Growth – $1,750/mo: 50GB/80K resources Enterprise – Custom: Unlimited, hybrid/on-prem	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	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
Documentation – docs.rag.progress.cloud SDK Ecosystem – Python 21K weekly + JavaScript Progress Support – 2,000+ employee parent company	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
⚠️ NO HIPAA – Healthcare PHI requires sales contact ⚠️ NO Messaging – No Slack, WhatsApp, Teams ⚠️ Acquisition Risk – June 2025 purchase, transitioning	⚠️ 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	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
Advanced R A G ( Core Differentiator)
N/A	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

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Final Thoughts

Final Verdict: Progress Agentic RAG vs RAGFlow

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

When to Choose Progress Agentic RAG

You value proprietary remi v2 model (30x faster inference) addresses hallucination problem with continuous quality monitoring - differentiated capability absent from most competitors
Open-source NucliaDB transparency (710+ GitHub stars) with managed infrastructure removes operational burden while maintaining technical visibility
Genuine no-code accessibility: business users (marketing, HR, legal, support) can deploy functional RAG pipelines in minutes via visual dashboard

Best For: Proprietary REMi v2 model (30x faster inference) addresses hallucination problem with continuous quality monitoring - differentiated capability absent from most competitors

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

Migration & Switching Considerations

Switching between Progress Agentic RAG and RAGFlow 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

Progress Agentic RAG starts at $700/month, while RAGFlow 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 Progress Agentic RAG and RAGFlow 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 25, 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.

Progress Agentic RAG vs RAGFlow