What are the main differences between Progress Agentic RAG and SciPhi R2R?

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. SciPhi R2R leads in State-of-the-art retrieval accuracy and Open-source with strong community with 89/100 overall rating and 92% 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 SciPhi R2R emphasizes Multimodal ingestion (.pdf, .json, .png, .mp3, etc.). Pricing differs by $700/month.

Which is better for enterprises: Progress Agentic RAG or SciPhi R2R?

Progress Agentic RAG offers SOC 2 compliance for enterprise security. HIPAA compliance varies - contact vendors for details. For scalability, SciPhi R2R supports on-premise deployment for maximum control. SciPhi R2R leads with 89/100 enterprise readiness score (83/100 enterprise features).

How much does Progress Agentic RAG cost vs SciPhi R2R?

Progress Agentic RAG starts at $700/monthly (paid model), while SciPhi R2R begins at contact sales/monthly (freemium model). SciPhi R2R 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 Progress Agentic RAG to SciPhi R2R?

Migration from Progress Agentic RAG to SciPhi R2R typically requires API-based data export/import, which SciPhi R2R provides. SciPhi R2R provides comprehensive API access excellent documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact SciPhi R2R support for migration assistance and best practices.

What integrations do Progress Agentic RAG and SciPhi R2R 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). SciPhi R2R supports OpenAI, Anthropic Claude, Local LLMs, PostgreSQL, S3 storage (10 integrations available). Both offer REST APIs for custom integrations. SciPhi R2R provides 43% more integrations, with webhook support for real-time data sync.

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

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

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

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

How much does Progress Agentic RAG cost vs SciPhi?

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

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

What integrations do Progress Agentic RAG and SciPhi support?

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

Progress Agentic RAG vs SciPhi

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

More about SciPhi 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 SciPhi 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 SciPhi, 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 SciPhi if: you value state-of-the-art retrieval accuracy

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 SciPhi

SciPhi is the most advanced ai retrieval system. R2R is a production-ready AI retrieval system supporting Retrieval-Augmented Generation with advanced features including multimodal ingestion, hybrid search, knowledge graphs, and a Deep Research API for multi-step reasoning across documents and the web. Founded in 2023, headquartered in San Francisco, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

89/100

Starting Price

Custom

Key Differences at a Glance

In terms of user ratings, SciPhi in overall satisfaction. From a cost perspective, SciPhi 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	SciPhi	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	Handles 40 + formats—from PDFs and spreadsheets to audio—at massive scale Reference. Async ingest auto-scales, crunching millions of tokens per second—perfect for giant corpora Benchmark details. Ingest via code or API, so you can tap proprietary databases or custom pipelines with ease.	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	Ships a REST RAG API—plug it into websites, mobile apps, internal tools, or even legacy systems. No off-the-shelf chat widget; you wire up your own front end API snippet.	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	Core RAG engine serves retrieval-grounded answers; hook it to your UI for multi-turn chat. Multi-lingual if the LLM you pick supports it. Lead-capture or human handoff flows are yours to build through the API.	✅ #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	Agentic RAG – Reasoning agent for autonomous research across documents/web with multi-step problem solving Advanced Toolset – Semantic search, metadata search, document retrieval, web search, web scraping capabilities Multi-Turn Context – Stateful dialogues maintaining conversation history via conversation_id for follow-ups Citation Transparency – Detailed responses with source citations for fact-checking and verification ⚠️ No Pre-Built UI – API-first platform requires custom front-end development ⚠️ No Lead Analytics – Lead capture and dashboards must be implemented at application layer	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	Advanced extras like GraphRAG and agentic flows push beyond basic Q&A Great fit for enterprises needing deeply customized, fully integrated AI solutions.	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	Fully bespoke—design any UI you want and skin it to match your brand. SciPhi focuses on the back end, so front-end look-and-feel is entirely up to you.	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	LLM-agnostic—GPT-4, Claude, Llama 2, you choose. Pick, fine-tune, or swap models anytime to balance cost and performance Model options.	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	REST API plus a Python client (`R2RClient`) handle ingest and query tasks Docs and GitHub repos offer deep dives and open-source starter code SciPhi GitHub.	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 search (dense + keyword) keeps retrieval fast and sharp. Knowledge-graph boosts (HybridRAG) drive up to 150 % better accuracy Sub-second latency—even at enterprise scale.	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	Add new sources, tweak retrieval, mix collections—everything’s programmable. Chain API calls, re-rank docs, or build full agentic flows	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	Free tier plus a $25/mo Dev tier for experiments. Enterprise plans with custom pricing and self-hosting for heavy traffic Pricing.	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	Customer data stays isolated in SciPhi Cloud; self-host for full control. Standard encryption in transit and at rest; tune self-hosted setups to meet any regulation.	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	Dev dashboard shows real-time logs, latency, and retrieval quality Dashboard. Hook into Prometheus, Grafana, or other tools for deep monitoring.	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	Community help via Discord and GitHub; Enterprise customers get dedicated support Open-source core encourages community contributions and integrations.	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	No no-code UI—built for devs to wire into their own front ends. Dashboard is utilitarian: good for testing and monitoring, not for everyday business users.	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 – HYBRID RAG-AS-A-SERVICE combining open-source R2R with managed SciPhi Cloud Core Mission – Bridge experimental RAG models to production-ready systems with deployment flexibility Developer Target – Built for OSS community, startups, enterprises emphasizing developer flexibility and control RAG Leadership – HybridRAG (150% accuracy), millions tokens/second, 40+ formats, sub-second latency ✅ Open-source R2R core on GitHub enables customization, portability, avoids vendor lock-in ⚠️ NO no-code features – No chat widgets, visual builders, pre-built integrations or dashboards	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	Market position – Developer-first RAG infrastructure combining open-source flexibility with managed cloud service Target customers – Dev teams needing high-performance RAG, enterprises requiring millions tokens/second ingestion Key competitors – LangChain/LangSmith, Deepset/Haystack, Pinecone Assistant, custom RAG implementations Competitive advantages – HybridRAG (150% accuracy boost), async auto-scaling, 40+ formats, sub-second latency Pricing advantage – Free tier + $25/mo Dev plan; open-source foundation enables cost optimization Use case fit – Massive document volumes, advanced RAG needs, self-hosting control requirements	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	LLM-Agnostic Architecture – GPT-4, GPT-3.5, Claude, Llama 2, and other open-source models Model Flexibility – Easy swapping to balance cost/performance without vendor lock-in Custom Support – Configure any LLM via API including fine-tuned or proprietary models Embedding Providers – Multiple embedding options for semantic search and vector generation ✅ Full control over temperature, max tokens, and generation parameters	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	HybridRAG Technology – Vector search + knowledge graphs for 150% accuracy improvement Hybrid Search – Dense vector + keyword with reciprocal rank fusion Agentic RAG – Reasoning agent for autonomous research across documents and web Multimodal Ingestion – 40+ formats (PDFs, spreadsheets, audio) at massive scale ✅ Millions of tokens/second async auto-scaling ingestion throughput ✅ Sub-second latency even at enterprise scale with optimized operations	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 Knowledge – Process millions of documents with knowledge graph relationships Support Automation – RAG-powered support bots with accurate, grounded responses Research & Analysis – Agentic RAG for autonomous research across collections and web Compliance & Legal – Large document repositories with precise citation tracking Internal Docs – Developer-focused RAG for code, API references, technical knowledge Custom AI Apps – API-first architecture integrates into any application or workflow	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	Data Isolation – Single-tenant architecture with isolated customer data in SciPhi Cloud Self-Hosting Option – On-premise deployment for complete data control in regulated industries Encryption Standards – TLS in transit, AES-256 at rest encryption Access Controls – Document-level granular permissions with role-based access control (RBAC) ✅ Open-source R2R core enables security audits and compliance validation ✅ Self-hosted deployments tunable for HIPAA, SOC 2, and other regulations	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	Free Tier – Generous no-credit-card tier for experimentation and development Developer Plan – $25/month for individual developers and small projects Enterprise Plans – Custom pricing based on scale, features, and support Self-Hosting – Open-source R2R available free (infrastructure costs only) ✅ Flat subscription pricing without per-query or per-document charges ✅ Managed cloud handles infrastructure, deployment, scaling, updates, maintenance	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	Comprehensive Docs – Detailed docs at r2r-docs.sciphi.ai covering all features and endpoints GitHub Repository – Active open-source development at github.com/SciPhi-AI/R2R with code examples Community Support – Discord community and GitHub issues for peer support Enterprise Support – Dedicated channels for enterprise customers with SLAs ✅ Python client (R2RClient) with extensive examples and starter code ✅ Developer dashboard with real-time logs, latency, and retrieval quality metrics	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	⚠️ Developer-Focused – Requires technical expertise to build and wire custom front ends ⚠️ Infrastructure Requirements – Self-hosting needs GPU infrastructure and DevOps expertise ⚠️ Integration Effort – API-first design means building your own chat UI ⚠️ Learning Curve – Advanced features like knowledge graphs require RAG concept understanding ⚠️ Community Support Limits – Open-source support relies on community unless enterprise plan	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

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Final Thoughts

Final Verdict: Progress Agentic RAG vs SciPhi

After analyzing features, pricing, performance, and user feedback, both Progress Agentic RAG and SciPhi 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 SciPhi

You value state-of-the-art retrieval accuracy
Open-source with strong community
Production-ready with proven scalability

Best For: State-of-the-art retrieval accuracy

Migration & Switching Considerations

Switching between Progress Agentic RAG and SciPhi 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 SciPhi 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 SciPhi 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 24, 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 SciPhi