In this comprehensive guide, we compare Progress Agentic RAG and Ragie 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 Ragie, 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 Ragie if: you value true multimodal support including audio/video
About Progress Agentic RAG
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 Ragie
Ragie is fully managed rag-as-a-service for developers. Ragie is a fully managed RAG-as-a-Service platform that enables developers to build AI applications connected to their data with simple APIs. Originally developed for Glue chat app, it offers multimodal support including audio/video RAG, advanced features like hybrid search, and seamless data source integrations. Founded in 2024, headquartered in San Francisco, CA, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
88/100
Starting Price
Custom
Key Differences at a Glance
In terms of user ratings, Ragie in overall satisfaction. From a cost perspective, Ragie 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
Ragie
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
60+ Document Formats: PDF, Word (.docx), Excel, PowerPoint, plain text, email formats with automatic parsing
Multimedia Processing: Automatic speech-to-text (MP3, WAV, AIFF), video transcript extraction (MP4, etc.), OCR for scanned documents/images
Cloud Connectors: SharePoint, Confluence, OneDrive, Google Drive, Amazon S3 with direct integration
Sync Agent Desktop App: 60-minute automatic sync with content hashing to prevent redundant reindexing
Manual Upload Interface: Files, folders, web links, sitemaps, Q&A pairs via dashboard
Fast Deployment: 2-hour initial ingestion, 48-hour full deployment timeline
CRITICAL GAPS: NO Dropbox integration, NO Notion integration, NO explicit YouTube transcript extraction documented
Architecture Focus: Comprehensive knowledge retrieval vs lead conversion focus (unlike Drift)
Comes with ready-made connectors for Google Drive, Gmail, Notion, Confluence, and more, so data syncs automatically.
Upload PDFs, DOCX, TXT, Markdown, or point it at a URL / sitemap to crawl an entire site and build your knowledge base.
Choose manual or automatic retraining, so your RAG stays up-to-date whenever content changes.
Lets you ingest more than 1,400 file formats—PDF, DOCX, TXT, Markdown, HTML, and many more—via simple drag-and-drop or API.
Crawls entire sites through sitemaps and URLs, automatically indexing public help-desk articles, FAQs, and docs.
Turns multimedia into text on the fly: YouTube videos, podcasts, and other media are auto-transcribed with built-in OCR and speech-to-text.
View Transcription Guide
Connects to Google Drive, SharePoint, Notion, Confluence, HubSpot, and more through API connectors or Zapier.
See Zapier Connectors
Supports both manual uploads and auto-sync retraining, so your knowledge base always stays up to date.
CSS Customization: Shadow DOM architecture with cssPath attribute for advanced styling
White-Labeling: Full OEM deployment support via API-first design
MISSING FEATURES: NO lead capture, NO human handoff/escalation workflows, NO proactive alerting (monitoring exists, alerting undocumented)
Agentic Retrieval: Next-generation multi-step retrieval engine designed for complex queries - decomposes questions, identifies relevant sources, self-checks results, compiles grounded answers with citations
Context-Aware MCP Server: Native Streamable HTTP MCP Server with Context-Aware descriptions enabling agents to understand actual knowledge base content for accurate tool routing
Multi-Step Reasoning: Agent-ready capabilities for breaking down complex queries into sequential retrieval operations with self-validation
Real-Time Indexing: Launch RAG pipelines for LLMs with immediate content updates and synchronization
Entity Extraction: Extract structured data from unstructured documents automatically for advanced querying
Summary Index: Avoid document affinity problems through intelligent summarization techniques
Multi-Turn Context: Maintains conversation history and context across dialogue turns for coherent multi-turn interactions
LIMITATION - No Built-In Chatbot UI: RAG-as-a-Service API platform requiring developers to build custom chat interfaces - not a turnkey chatbot solution
LIMITATION - No Lead Capture/Handoff: Focuses on retrieval infrastructure - lead generation and human escalation must be implemented at application layer
Custom AI Agents: Build autonomous agents powered by GPT-4 and Claude that can perform tasks independently and make real-time decisions based on business knowledge
Decision-Support Capabilities: AI agents analyze proprietary data to provide insights, recommendations, and actionable responses specific to your business domain
Multi-Agent Systems: Deploy multiple specialized AI agents that can collaborate and optimize workflows in areas like customer support, sales, and internal knowledge management
Memory & Context Management: Agents maintain conversation history and persistent context for coherent multi-turn interactions
View Agent Documentation
Tool Integration: Agents can trigger actions, integrate with external APIs via webhooks, and connect to 5,000+ apps through Zapier for automated workflows
Hyper-Accurate Responses: Leverages advanced RAG technology and retrieval mechanisms to deliver context-aware, citation-backed responses grounded in your knowledge base
Continuous Learning: Agents improve over time through automatic re-indexing of knowledge sources and integration of new data without manual retraining
Additional Considerations
Recent Acquisition (June 2025): Progress Software acquired Nuclia for $50M - platform transitioning under new ownership with potential strategic direction changes
Genuine No-Code + Developer Appeal: Dual-track value proposition - non-technical teams use dashboard, developers leverage API/SDKs for custom builds
REMi Quality Differentiator: Proprietary continuous evaluation model (30x faster in v2) addresses hallucination problem absent from most RAG competitors
Open-Source Trust Factor: NucliaDB (710+ GitHub stars, AGPLv3) provides code transparency vs black-box platforms - security audits possible
Multimodal Strength: OCR for images, speech-to-text for audio/video creates comprehensive searchable corpus beyond text-only competitors
Enterprise RAG Focus: Platform optimized for knowledge retrieval and semantic search - not conversational marketing/sales engagement like Drift/Yellow.ai
Progress Ecosystem Integration: OpenEdge database connector, Sitefinity CMS integration provides distribution channels unavailable to standalone platforms
Documentation Fragmentation: Dual portals (docs.rag.progress.cloud + legacy docs.nuclia.dev) during transition may cause developer confusion
Competitive Pricing Entry: $700/month Fly tier undercuts enterprise RAG alternatives while providing genuine capabilities vs limited free tiers
Best For: Organizations wanting model flexibility (7 providers), multimodal indexing, open-source transparency, and developer API access without managing infrastructure
"Functions" feature lets the bot perform real actions (e.g., make a ticket) right in the chat.
Headless RAG API (SourceSync) gives devs a fully customizable retrieval layer.
Slashes engineering overhead with an all-in-one RAG platform—no in-house ML team required.
Gets you to value quickly: launch a functional AI assistant in minutes.
Stays current with ongoing GPT and retrieval improvements, so you’re always on the latest tech.
Balances top-tier accuracy with ease of use, perfect for customer-facing or internal knowledge projects.
Customization & Branding
Prompt Lab: Test LLMs side-by-side using actual customer data with real-time comparison
Four Index Types: Document Index (property filtering), Full Text (keyword/fuzzy search), Chunk/Vector (semantic similarity), Knowledge Graph (entity relationships)
Dynamic Sharding: Automatic shard creation as vectors grow with index node replication for fault tolerance
Open-Source Transparency: NucliaDB foundation (710+ GitHub stars) provides visibility into retrieval mechanisms vs black-box platforms (Lindy.ai)
Comparison Alignment: Direct architectural comparison to CustomGPT.ai is valid - both are RAG-as-a-Service platforms with API-first design
Use Case Fit: Organizations prioritizing knowledge retrieval, semantic search, and generative Q&A over conversational marketing/sales engagement
Platform Type: TRUE RAG-AS-A-SERVICE API PLATFORM - fully managed developer-first infrastructure announced August 2024 with $5.5M seed funding
Core Mission: Enable developers to build AI applications connected to their own data with outstanding RAG results in record time using managed infrastructure
Developer Target Market: Built by industry veterans (Bob Remeika, Mohammed Rafiq) for development teams requiring production-grade RAG without infrastructure management
API-First Architecture: TypeScript and Python SDKs with robust data ingest pipeline and retrieval API using latest RAG techniques for chunking, searching, re-ranking
RAG Technology Leadership: Advanced features include Summary Index (avoiding document affinity), Entity Extraction (structured data from unstructured), Agentic Retrieval (multi-step reasoning), Context-Aware MCP Server
Managed Service Benefits: Free developer tier, pro plan for production, enterprise for scale - eliminates infrastructure complexity while maintaining developer control
Security & Compliance: AES-256 storage, TLS transmission, GDPR/SOC 2 Type II/HIPAA/CASA/CCPA certified - zero customer data usage for model training
Data Source Integration: Ragie Connect handles authentication and auto-sync from Google Drive, Salesforce, Notion, Confluence with real-time indexing
LIMITATION vs No-Code Platforms: NO native chat widgets, Slack/WhatsApp integrations, visual chatbot builders, analytics dashboards, or lead capture/handoff - requires custom UI development
Comparison Validity: Architectural comparison to CustomGPT.ai is VALID but highlights different priorities - Ragie.ai managed RAG infrastructure vs CustomGPT likely more accessible no-code deployment
Use Case Fit: Development teams building custom RAG applications requiring managed infrastructure, enterprises needing production-grade retrieval with agent-ready capabilities, organizations wanting security compliance without infrastructure overhead
NOT Ideal For: Non-technical teams seeking turnkey chatbot solutions, businesses requiring pre-built UI widgets, organizations needing immediate deployment without developer resources
Core Architecture: Serverless RAG infrastructure with automatic embedding generation, vector search optimization, and LLM orchestration fully managed behind API endpoints
API-First Design: Comprehensive REST API with well-documented endpoints for creating agents, managing projects, ingesting data (1,400+ formats), and querying chat
API Documentation
Developer Experience: Open-source Python SDK (customgpt-client), Postman collections, OpenAI API endpoint compatibility, and extensive cookbooks for rapid integration
No-Code Alternative: Wizard-style web dashboard enables non-developers to upload content, brand widgets, and deploy chatbots without touching code
Hybrid Target Market: Serves both developer teams wanting robust APIs AND business users seeking no-code RAG deployment - unique positioning vs pure API platforms (Cohere) or pure no-code tools (Jotform)
RAG Technology Leadership: Industry-leading answer accuracy (median 5/5 benchmarked), 1,400+ file format support with auto-transcription, proprietary anti-hallucination mechanisms, and citation-backed responses
Benchmark Details
Deployment Flexibility: Cloud-hosted SaaS with auto-scaling, API integrations, embedded chat widgets, ChatGPT Plugin support, and hosted MCP Server for Claude/Cursor/ChatGPT
Enterprise Readiness: SOC 2 Type II + GDPR compliance, full white-labeling, domain allowlisting, RBAC with 2FA/SSO, and flat-rate pricing without per-query charges
Use Case Fit: Ideal for organizations needing both rapid no-code deployment AND robust API capabilities, teams handling diverse content types (1,400+ formats, multimedia transcription), and businesses requiring production-ready RAG without building ML infrastructure from scratch
Competitive Positioning: Bridges the gap between developer-first platforms (Cohere, Deepset) requiring heavy coding and no-code chatbot builders (Jotform, Kommunicate) lacking API depth - offers best of both worlds
Competitive Positioning
Market Position: Enterprise RAG-as-a-Service with genuine no-code accessibility + developer-first API design (dual-track appeal)
vs. CustomGPT: Similar RAG-as-a-Service category, Progress emphasizes REMi quality monitoring + open-source foundation differentiation
vs. Drift/Yellow.ai: TRUE RAG platform vs conversational marketing/sales engagement platforms (fundamentally different categories)
vs. Lindy.ai: Full API/SDK access vs NO public API (Progress developer-friendly, Lindy no-code only)
Integration Gaps: NO native messaging channels (Slack/WhatsApp/Teams) vs omnichannel competitors - requires custom development
HIPAA Gap: No documented certification creates healthcare trust gap vs compliant competitors (Drift has HIPAA)
Recent Acquisition Risk: June 2025 Progress purchase means platform still maturing under new ownership with potential direction changes
Progress Ecosystem Advantage: Integration with OpenEdge, Sitefinity CMS provides distribution channels unavailable to standalone competitors
Market position: Developer-friendly RAG platform balancing no-code dashboard usability with API flexibility, focused on customer support workflows and multi-channel deployment
Target customers: Small to mid-size businesses needing quick chatbot deployment, support teams requiring multi-channel presence (Slack, Telegram, WhatsApp, Messenger, Teams), and developers wanting flexible API with straightforward pricing
Key competitors: Chatbase.co, Botsonic, SiteGPT, CustomGPT, and other SMB-focused no-code chatbot platforms
Competitive advantages: Hybrid search with re-ranking and smart partitioning for improved accuracy, headless SourceSync API for custom RAG backends, "Functions" feature enabling bot actions (tickets, CRM updates), 95+ language support, ready-made Google Drive/Gmail/Notion/Confluence connectors, and flexible mode switching between "fast" (GPT-4o-mini) and "accurate" (GPT-4o)
Pricing advantage: Mid-range at ~$79/month (Growth) and ~$259/month (Pro/Scale); straightforward tiered pricing without confusing jumps; scales smoothly with message credits and capacity add-ons; best value for growing teams needing multi-channel support
Use case fit: Ideal for support teams needing multi-channel chatbot deployment (Slack, WhatsApp, Teams, Messenger, Telegram), developers wanting simple REST API without heavy SDK requirements, and SMBs requiring webhook/Zapier automation for CRM and ticket system integration
Market position: Leading all-in-one RAG platform balancing enterprise-grade accuracy with developer-friendly APIs and no-code usability for rapid deployment
Target customers: Mid-market to enterprise organizations needing production-ready AI assistants, development teams wanting robust APIs without building RAG infrastructure, and businesses requiring 1,400+ file format support with auto-transcription (YouTube, podcasts)
Key competitors: OpenAI Assistants API, Botsonic, Chatbase.co, Azure AI, and custom RAG implementations using LangChain
Competitive advantages: Industry-leading answer accuracy (median 5/5 benchmarked), 1,400+ file format support with auto-transcription, SOC 2 Type II + GDPR compliance, full white-labeling included, OpenAI API endpoint compatibility, hosted MCP Server support (Claude, Cursor, ChatGPT), generous data limits (60M words Standard, 300M Premium), and flat monthly pricing without per-query charges
Pricing advantage: Transparent flat-rate pricing at $99/month (Standard) and $449/month (Premium) with generous included limits; no hidden costs for API access, branding removal, or basic features; best value for teams needing both no-code dashboard and developer APIs in one platform
Use case fit: Ideal for businesses needing both rapid no-code deployment and robust API capabilities, organizations handling diverse content types (1,400+ formats, multimedia transcription), teams requiring white-label chatbots with source citations for customer-facing or internal knowledge projects, and companies wanting all-in-one RAG without managing ML infrastructure
Deployment & Infrastructure
Fully Managed Cloud: EU (primary) and US data centers with regional API routing (https://{region}.rag.progress.cloud/api/v1/)
Hybrid Deployment: Cloud processing with on-premise NucliaDB storage for data sovereignty requirements
Complete On-Premise: Enterprise tier supports 100% on-premise deployment for maximum data governance
AWS Marketplace: Available November 2025 for streamlined enterprise procurement with existing cloud spend
Dynamic Scaling: Automatic shard creation as vector counts grow with index node replication
Web Component Embedding: <nuclia-search-bar> and <nuclia-chat> for website integration
Multi-Region Support: Regional data residency options (EU/US) for compliance requirements
N/A
N/A
Customer Base & Case Studies
SRS Distribution (Wholesale Building Materials): "Progress Agentic RAG has fundamentally changed how we access and act on information across our organisation. Its ability to deliver fast, accurate, and verifiable insights from our unstructured data has been a game-changer for productivity and decision-making."
BrokerChooser (Financial Services): Replaced keyword search with generative AI, reporting significant conversion increases and better user experience
NAFEMS (Engineering Simulation Association): Knowledge discovery across thousands of technical publications for international membership community
Althaia Hospitals (Spain's Largest Central Catalonia Hospital): Medical protocol search supporting 5,000+ healthcare professionals
Columbia Business School: Academic knowledge discovery and research support
Barry University: Education sector deployment for institutional knowledge management
CCOO (Spain's Largest Trade Union): 1M+ members served with knowledge retrieval platform
Buff Sportswear: Commercial deployment for product and customer knowledge management
Pre-Acquisition Scale: ~20 customers across healthcare, pharmaceutical, education, public administration sectors
N/A
N/A
A I Models
Anthropic Models: Claude 3.7, Claude 3.5 Sonnet v2 for safety-focused, high-quality generation
OpenAI Models: ChatGPT 4o, 4o mini for industry-leading language capabilities
Google Models: Gemini Flash 2.5, PaLM2 for multimodal and search-optimized tasks
Meta Models: Llama 3.2 for open-source flexibility and customization
Microsoft/Azure: Mistral Large 2 for enterprise deployments with Azure integration
Cohere Models: Command-R suite for retrieval-optimized generation
Nuclia Private GenAI: 100% data isolation mode for maximum security without third-party LLM exposure
Model Switching: Change providers without architectural changes via Prompt Lab for side-by-side testing
OpenAI GPT-4o: Primary "accurate" mode for depth and comprehensive analysis - highest quality responses with advanced reasoning
OpenAI GPT-4o-mini: "Fast" mode for speed-optimized responses - balances quality with rapid response times for high-volume scenarios
Claude 3.5 Sonnet Integration: Confirmed support through RAG-as-a-Service architecture - enables Anthropic Claude model deployment for production systems
Flexible Model Selection: Switch between "fast" and "accurate" modes per chatbot configuration - adapt to specific use case requirements
Mode Toggle: Simple dashboard control to flip between GPT-4o-mini (speed) and GPT-4o (depth) without code changes
2024 Model Support: Updated for latest models including gpt-4o-mini with improved long-context behavior and minimal performance deterioration
Performance Optimization: Modern LLMs (gpt-4o, claude-3.5-sonnet, gpt-4o-mini) show little to no degradation as context length increases - ideal for RAG applications
No Model Agnosticism: Focused on OpenAI and Claude ecosystems - not designed for Llama, Mistral, or custom model deployment
Automatic Updates: Platform maintains compatibility with latest OpenAI and Anthropic model releases automatically
Primary models: GPT-5.1 and 4 series from OpenAI, and Anthropic's Claude 4.5 (opus and sonnet) for enterprise needs
Automatic model selection: Balances cost and performance by automatically selecting the appropriate model for each request
Model Selection Details
Proprietary optimizations: Custom prompt engineering and retrieval enhancements for high-quality, citation-backed answers
Managed infrastructure: All model management handled behind the scenes - no API keys or fine-tuning required from users
Anti-hallucination technology: Advanced mechanisms ensure chatbot only answers based on provided content, improving trust and factual accuracy
R A G Capabilities
Agentic RAG Engine: Retrieval agents autonomously select optimal strategies based on query characteristics
Four-Index Hybrid Search: Document (property filtering), Full Text (keyword/fuzzy), Vector/Chunk (semantic), Knowledge Graph (entity relationships)
Dynamic Knowledge Management: Continuous updates, gap identification, and automatic documentation generation
Developer RAG Backend: API-first infrastructure for building custom AI applications with Prompt Lab experimentation
Customer Support Chatbots: Deploy self-service bots retrieving accurate answers from help articles, manuals, past tickets - reduce support ticket volume up to 70%
Internal AI Assistants: Power employee-facing assistants with company-specific knowledge from Google Drive, Notion, Confluence - instant answers across enterprise tools
Multi-Channel Support: Unified chatbot deployment across Slack, Telegram, WhatsApp, Facebook Messenger, Microsoft Teams - consistent support experience everywhere
Website Chat Widgets: Embed conversational AI on websites for real-time customer engagement, lead capture, and instant question answering
Sales Enablement: Surface relevant product data and customer interaction insights for sales teams - precise, high-recall retrieval from sales collateral
Legal Research Tools: Query legal texts and regulatory frameworks with high accuracy and contextual understanding - cite sources transparently
Compliance & Policy Assistants: Internal bots answering employee questions about company policies, compliance requirements, HR procedures from knowledge bases
Product Documentation: Technical documentation chatbots for developers and customers - quick answers from API docs, tutorials, troubleshooting guides
Educational Assistants: Course material Q&A, student support, academic research assistance with citation-backed responses from course content
CRM Integration: "Functions" feature enables bots to create tickets, update CRM records, trigger workflows directly from chat conversations
Enterprise SaaS Products: Embed RAG-powered assistance into SaaS applications for context-rich user support and feature discovery
Customer support automation: AI assistants handling common queries, reducing support ticket volume, providing 24/7 instant responses with source citations
Internal knowledge management: Employee self-service for HR policies, technical documentation, onboarding materials, company procedures across 1,400+ file formats
Sales enablement: Product information chatbots, lead qualification, customer education with white-labeled widgets on websites and apps
Documentation assistance: Technical docs, help centers, FAQs with automatic website crawling and sitemap indexing
Educational platforms: Course materials, research assistance, student support with multimedia content (YouTube transcriptions, podcasts)
Healthcare information: Patient education, medical knowledge bases (SOC 2 Type II compliant for sensitive data)
E-commerce: Product recommendations, order assistance, customer inquiries with API integration to 5,000+ apps via Zapier
SaaS onboarding: User guides, feature explanations, troubleshooting with multi-agent support for different teams
Security & Compliance
SOC2 Type 2: Annually audited for enterprise security assurance
ISO 27001: Annually audited information security management certification
GDPR Compliant: Built-in PII anonymization automatically detects and removes personal data
Encryption: AES-256 at rest, TLS in transit for comprehensive data protection
AI Risk Classification: Low to minimal AI risk category with policy-as-code guardrails
Human-in-the-Loop: Validation options for critical workflows requiring human oversight
Tenant Isolation: Customer data separation ensures multi-tenant security with isolated Knowledge Boxes
Audit Logs: Standard across all pricing tiers for compliance tracking and security monitoring
API Key Management: Temporal keys and rotation for security hygiene
CRITICAL LIMITATION: NO HIPAA certification documented - healthcare organizations processing PHI must contact sales for compliance clarification
Data Governance: Enterprise tier supports complete on-premise deployment for 100% data control and sovereignty
HTTPS/TLS Encryption: Industry-standard transport layer security encrypting all data in transit between clients and servers
Data at Rest Encryption: Encrypted storage protecting customer data and knowledge bases from unauthorized access
Workspace Data Isolation: Customer data stays isolated within dedicated workspaces - no cross-tenant information leakage
SOC 2 Roadmap: Formal SOC 2 Type II certification in progress - planned compliance milestone for enterprise customers
GDPR Considerations: Data handling aligns with GDPR principles - customer data processing under user control
Domain Allowlisting: Lock chatbots to approved domains for enhanced security - prevent unauthorized embedding or access
Access Controls: Dashboard-level permissions and API key management for secure multi-user team access
Data Retention: Configurable data retention policies for conversation histories and uploaded documents
Audit Logging: Activity tracking for compliance monitoring and security incident investigation
Third-Party Dependencies: Relies on OpenAI and Anthropic cloud APIs - inherits their security certifications (OpenAI SOC 2 Type II, Anthropic security standards)
No On-Premise Option: Cloud-only SaaS deployment - not suitable for air-gapped or on-premise requirements
Data Processing Agreement: Standard DPA available for enterprise customers requiring contractual data protection commitments
Encryption: SSL/TLS for data in transit, 256-bit AES encryption for data at rest
SOC 2 Type II certification: Industry-leading security standards with regular third-party audits
Security Certifications
GDPR compliance: Full compliance with European data protection regulations, ensuring data privacy and user rights
Access controls: Role-based access control (RBAC), two-factor authentication (2FA), SSO integration for enterprise security
Data isolation: Customer data stays isolated and private - platform never trains on user data
Domain allowlisting: Ensures chatbot appears only on approved sites for security and brand protection
Secure deployments: ChatGPT Plugin support for private use cases with controlled access
Pricing & Plans
Fly Tier: $700/month - 10GB/15K resources, 750MB max file, 1 Knowledge Box, cloud only, 10K tokens/month included
Scaling Consideration: Token-based consumption pricing requires careful usage forecasting for budget predictability beyond included tier
Best Value For: Organizations wanting to control costs through usage optimization vs fixed seat-based or per-project pricing models
Free Trial: 7-day free trial with full feature access - test everything risk-free before commitment
Growth Plan: ~$79/month - ideal for small teams starting with chatbot deployment and basic multi-channel support
Pro/Scale Plan: ~$259/month - expanded capacity with increased message credits, bots, pages crawled, and file uploads
Enterprise Plan: Custom pricing for large deployments - tailored capacity, dedicated support, SLA commitments
Message Credits System: Pay for usage through message credits - scales costs with actual chatbot utilization
Capacity Scaling: Add message credits, additional bots, crawl pages, and upload limits as you grow - no plan switching required
Multi-Bot Support: Spin up multiple chatbots under one account - manage different teams, domains, or use cases independently
Smooth Scaling: Designed to scale costs predictably without linear cost explosions - efficient pricing for growing businesses
Transparent Pricing: Straightforward tiered structure without hidden fees or confusing per-feature charges
Cost Predictability: Fixed monthly subscription with capacity limits - budget-friendly for SMBs vs unpredictable pay-per-API-call models
Best Value: Mid-range pricing competitive with Chatbase, SiteGPT, Botsonic - best value for multi-channel support teams
Annual Discounts: Likely available for annual commitments - standard SaaS discount practices apply
Standard Plan: $99/month or $89/month annual - 10 custom chatbots, 5,000 items per chatbot, 60 million words per bot, basic helpdesk support, standard security
View Pricing
Premium Plan: $499/month or $449/month annual - 100 custom chatbots, 20,000 items per chatbot, 300 million words per bot, advanced support, enhanced security, additional customization
Enterprise Plan: Custom pricing - Comprehensive AI solutions, highest security and compliance, dedicated account managers, custom SSO, token authentication, priority support with faster SLAs
Enterprise Solutions
7-Day Free Trial: Full access to Standard features without charges - available to all users
Annual billing discount: Save 10% by paying upfront annually ($89/mo Standard, $449/mo Premium)
Flat monthly rates: No per-query charges, no hidden costs for API access or white-labeling (included in all plans)
Managed infrastructure: Auto-scaling cloud infrastructure included - no additional hosting or scaling fees
Active community: User community plus 5,000+ app integrations through Zapier ecosystem
Regular updates: Platform stays current with ongoing GPT and retrieval improvements automatically
Limitations & Considerations
NO HIPAA Certification Documented: Healthcare organizations processing PHI must contact sales - major compliance gap vs competitors with documented HIPAA
NO Native Messaging Channels: No Slack, WhatsApp, Telegram, or Microsoft Teams integrations - requires custom API-based development
Documentation Fragmentation: Dual portals (docs.rag.progress.cloud + docs.nuclia.dev) during Progress acquisition transition may cause confusion
Recent Acquisition Risk: June 2025 Progress purchase means platform still maturing under new ownership with potential direction changes
Scalability Concerns: Multiple problems limit scalability - hard to scale nodes up/down, write operations affect concurrent search performance
NO Dropbox Integration: Missing Dropbox connector vs competitors - limits cloud storage sync options
NO Notion Integration: Missing Notion connector - gap for knowledge management workflows
NO YouTube Transcript Extraction: Not explicitly documented vs competitors with video indexing features
Missing Features: NO lead capture, NO human handoff/escalation workflows, NO proactive alerting (monitoring exists, alerting undocumented)
Learning Curve: 30+ RAG parameters and Prompt Lab may feel technical for non-developer teams despite no-code dashboard
Best For: Development teams and technical users - powerful for experts but may overwhelm business users wanting simple deployment
No Multi-Language SDKs: REST API only - no official Python, JavaScript, Java SDKs yet; developers must use raw HTTP requests
OpenAI/Claude Dependency: Tied to OpenAI and Anthropic models - cannot deploy Llama, Mistral, or custom open-source models
Cloud-Only Deployment: SaaS-only platform - no self-hosting, on-premise, or air-gapped deployment options for regulated industries
Limited Model Selection: Only GPT-4o and GPT-4o-mini toggle - no granular model selection or multi-model routing based on query complexity
No Enterprise Certifications: SOC 2 Type II on roadmap but not yet achieved - may disqualify for enterprise procurement requiring active certifications
Message Credit Limits: Plans have message credit caps - high-volume scenarios require plan upgrades or Enterprise custom pricing
Crawler Limitations: URL and sitemap crawling scope limited by plan tier - large websites may require higher tiers
No Advanced Analytics: Basic dashboard metrics - not as comprehensive as dedicated analytics platforms for deep conversation analysis
Retraining Workflow: Manual retraining required unless automatic mode enabled - knowledge base updates not always real-time
Functions Feature Complexity: "Functions" for bot actions (tickets, CRM) require technical setup - not fully no-code for advanced workflows
Limited Customization: Moderate UI customization - not as extensive as fully white-labeled or completely custom-built solutions
No Advanced RAG Features: Missing GraphRAG, knowledge graphs, agentic workflows, or advanced retrieval strategies found in developer-first platforms
Support Response Times: Email-based support may be slower than platforms offering live chat or phone support on standard plans
Emerging Platform: Newer platform vs established competitors - smaller ecosystem of integrations and third-party tools
Managed service approach: Less control over underlying RAG pipeline configuration compared to build-your-own solutions like LangChain
Vendor lock-in: Proprietary platform - migration to alternative RAG solutions requires rebuilding knowledge bases
Model selection: Limited to OpenAI (GPT-5.1 and 4 series) and Anthropic (Claude, opus and sonnet 4.5) - no support for other LLM providers (Cohere, AI21, open-source models)
Pricing at scale: Flat-rate pricing may become expensive for very high-volume use cases (millions of queries/month) compared to pay-per-use models
Customization limits: While highly configurable, some advanced RAG techniques (custom reranking, hybrid search strategies) may not be exposed
Language support: Supports 90+ languages but performance may vary for less common languages or specialized domains
Real-time data: Knowledge bases require re-indexing for updates - not ideal for real-time data requirements (stock prices, live inventory)
Enterprise features: Some advanced features (custom SSO, token authentication) only available on Enterprise plan with custom pricing
After analyzing features, pricing, performance, and user feedback, both Progress Agentic RAG and Ragie 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 Ragie
You value true multimodal support including audio/video
Extremely developer-friendly with simple APIs
Fully managed service - no infrastructure hassle
Best For: True multimodal support including audio/video
Migration & Switching Considerations
Switching between Progress Agentic RAG and Ragie 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 Ragie 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 Ragie 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: December 11, 2025 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.
The most accurate RAG-as-a-Service API. Deliver production-ready reliable RAG applications faster. Benchmarked #1 in accuracy and hallucinations for fully managed RAG-as-a-Service API.
DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.
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