Progress Agentic RAG vs Pyx

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

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Priyansh Khodiyar's avatar
Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare Progress Agentic RAG and Pyx 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 Pyx, 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 Pyx if: you value very quick setup (30-60 minutes)

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 Pyx

Pyx Landing Page Screenshot

Pyx is find. don't search.. Pyx AI is an enterprise conversational search tool that leverages Retrieval-Augmented Generation (RAG) to deliver real-time answers from company data. It continuously synchronizes with data sources and enables natural language queries across unstructured documents without keywords or pre-sorting. Founded in 2022, headquartered in Europe, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
83/100
Starting Price
$30/mo

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, Pyx offers more competitive entry pricing. The platforms also differ in their primary focus: Enterprise Software versus AI Search. These differences make each platform better suited for specific use cases and organizational requirements.

⚠️ What This Comparison Covers

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

Detailed Feature Comparison

logo of progress
Progress Agentic RAG
logo of pyx
Pyx
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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)
  • Focuses on unstructured data—you simply point it at your files and it indexes them right away. Appvizer mention
  • Keeps connected file repositories in sync automatically, so any document changes show up almost instantly.
  • Works with common formats (PDF, DOCX, PPT, text, and more) and turns them into a chat-ready knowledge store.
  • Doesn’t try to crawl whole websites or YouTube—the ingestion scope is intentionally narrower than CustomGPT’s.
  • Built for enterprise-scale volumes (exact limits not published) and aims for near-real-time indexing of large corporate data sets.
  • 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.
Integrations & Channels
  • Python SDK: pip install nuclia (Python 3.8+, ~21,000 weekly downloads)
  • JavaScript/TypeScript SDK: @nuclia/core on NPM (React, Next.js, Angular, Vue.js, Svelte)
  • CMS Plugins: WordPress, Strapi integrations
  • Workflow Automation: Pipedream official app, Zapier API-compatible
  • Chrome Extension: Web page indexing capability
  • Progress Ecosystem: OpenEdge database connector, Sitefinity CMS integration ('first Generative CMS')
  • CRITICAL LIMITATION: NO native Slack, WhatsApp, Telegram, or Microsoft Teams integrations
  • Platform Design: RAG backend + embeddable widget, NOT omnichannel conversational AI platform
  • Custom Development Required: Messaging platform integrations need API-based custom builds
  • Comes with its own chat/search interface rather than a “deploy everywhere” model.
  • No built-in Slack bot, Zapier connector, or public API for external embeds.
  • Most users interact through Pyx’s web or desktop UI; synergy with other chat platforms is minimal for now.
  • Any deeper integration (say, Slack commands) would require custom dev work or future product updates.
  • Embeds easily—a lightweight script or iframe drops the chat widget into any website or mobile app.
  • Offers ready-made hooks for Slack, Zendesk, Confluence, YouTube, Sharepoint, 100+ more. Explore API Integrations
  • Connects with 5,000+ apps via Zapier and webhooks to automate your workflows.
  • Supports secure deployments with domain allowlisting and a ChatGPT Plugin for private use cases.
  • Hosted CustomGPT.ai offers hosted MCP Server with support for Claude Web, Claude Desktop, Cursor, ChatGPT, Windsurf, Trae, etc. Read more here.
  • Supports OpenAI API Endpoint compatibility. Read more here.
Core Chatbot Features
  • AI Search & Generative Answers: Semantic search and Q&A across knowledge bases with trusted, source-linked answers
  • Multi-Turn Conversations: Context-aware dialogue with conversation history maintained for follow-up questions
  • Source Citations: Every answer includes citations linking to source documents for verification and transparency
  • Auto-Summarization: Automatic summarization of long documents for quick understanding
  • Entity Recognition: AI classification and entity extraction enriching corpus for better Q&A
  • Answer-Only Mode: Widget configuration for concise answers vs detailed responses based on use case
  • Multilingual Support: Nuclia multilingual embedding model handles multiple languages out-of-box
  • MISSING FEATURES: NO lead capture, NO human handoff/escalation workflows, NO chat history export for users
  • Delivers conversational search over enterprise documents and keeps track of context for follow-up questions. Appvizer reference
  • Geared toward internal knowledge management—features like lead capture or human handoff aren’t part of the roadmap.
  • Likely supports multiple languages to some extent, though it’s not a headline feature the way it is for CustomGPT.
  • Stores chat history inside the interface, but offers fewer business-oriented analytics than products with customer-facing use cases.
  • Reduces hallucinations by grounding replies in your data and adding source citations for transparency. Benchmark Details
  • Handles multi-turn, context-aware chats with persistent history and solid conversation management.
  • Speaks 90+ languages, making global rollouts straightforward.
  • Includes extras like lead capture (email collection) and smooth handoff to a human when needed.
Core Agent Features
  • Retrieval Agents: Autonomously select optimal retrieval strategies based on query characteristics
  • Pre-Built Ingestion Agents (Beta): Labeler (auto-classification), Generator (summaries/JSON/extraction), Graph Extraction (entities/relationships), Q&A Generator (automatic FAQ), Content Safety (inappropriate content flagging)
  • Web Components: <nuclia-search-bar> and <nuclia-chat> for website embedding
  • Widget Configuration: Point-and-click for suggestions, filters, metadata display, thumbnails, answer-only modes
  • 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)
  • NO Agent Capabilities: Pyx AI does not offer autonomous agents, tool calling, or multi-agent orchestration features
  • Conversational Search Only: Provides context-aware dialogue for internal knowledge Q&A - not agentic behavior or autonomous decision-making
  • Basic RAG Architecture: Standard retrieval-augmented generation without agent-specific enhancements (no function calling, no tool use, no workflows)
  • Follow-Up Questions: Maintains conversation context for multi-turn dialogue but no autonomous reasoning or task execution capabilities
  • Closed System: Standalone application without extensibility for agent frameworks (LangChain, CrewAI) or external tool integration
  • Auto-Sync Automation: Connected file repositories auto-sync (automation feature) but not agent-driven - simple scheduled indexing
  • No External Actions: Cannot invoke APIs, execute code, query databases, or interact with external systems - pure knowledge retrieval
  • Internal Knowledge Focus: Designed for employee Q&A about company documents - not task automation or agentic workflows
  • Platform Philosophy: Intentionally simple scope with minimal configuration - avoids complexity of agentic systems
  • Use Case Limitation: Suitable for knowledge search only - not for autonomous agents, workflow automation, or complex reasoning tasks
  • 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
  • Great if you want a no-fuss, internal knowledge chat that employees can use without coding.
  • Not ideal for public-facing chatbots or developer-heavy customization.
  • Shines as a single, siloed AI search environment rather than a broad, extensible platform.
  • Simpler in scope than CustomGPT—less flexible, but easier to stand up quickly for internal use cases.
  • 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
  • 30+ RAG Parameters: Custom chunking strategies, context size configuration, hybrid search weighting
  • Retrieval Strategy Customization: Agents autonomously select optimal approaches per query
  • Widget Customization: Visual editor for suggestions, filters, metadata, thumbnails, answer modes
  • Advanced CSS Styling: Shadow DOM with cssPath attribute for deep customization
  • White-Labeling Support: Full OEM deployments via API-first architecture
  • Role-Based Access Control: Account-level (Owners, Members), Knowledge Box-level (Manager, Writer, Reader) with cascading permissions
  • SSO Integration: Enterprise identity provider connectivity
  • Designed as an internal tool with its own UI, so only minimal branding tweaks (logo/colors) are available.
  • No white-label or domain-embed options—Pyx lives as a standalone interface rather than a widget on your site.
  • The look and feel stay “Pyx AI” by design; public-facing brand alignment isn’t the goal here.
  • Emphasis is on security and user management over front-end theming.
  • Fully white-labels the widget—colors, logos, icons, CSS, everything can match your brand. White-label Options
  • Provides a no-code dashboard to set welcome messages, bot names, and visual themes.
  • Lets you shape the AI’s persona and tone using pre-prompts and system instructions.
  • Uses domain allowlisting to ensure the chatbot appears only on approved sites.
L L M Model Options
  • Anthropic: Claude 3.7, Claude 3.5 Sonnet v2
  • OpenAI: ChatGPT 4o, 4o mini
  • Google: Gemini Flash 2.5, Palm2
  • Meta: Llama 3.2
  • Microsoft/Azure: Mistral Large 2
  • Cohere: Command-R suite
  • Nuclia Private GenAI: 100% data isolation for maximum security
  • Model Switching: Change providers without architectural changes via Prompt Lab
  • Embedding Flexibility: Configurable per Knowledge Box (Nuclia multilingual default + OpenAI embeddings)
  • Side-by-Side Testing: Compare responses across models using actual data in Prompt Lab
  • Doesn’t expose model choice—Pyx likely runs GPT-3.5 or GPT-4 under the hood, but you can’t switch or fine-tune it.
  • No toggles for speed vs. accuracy; every query uses the same model configuration.
  • Focuses on its RAG engine with a single, undisclosed LLM—less flexible than tools that let you pick GPT-3.5 or GPT-4 explicitly.
  • No advanced re-ranking or multi-model routing options are mentioned.
  • Taps into top models—OpenAI’s GPT-5.1 series, GPT-4 series, and even Anthropic’s Claude for enterprise needs (4.5 opus and sonnet, etc ).
  • Automatically balances cost and performance by picking the right model for each request. Model Selection Details
  • Uses proprietary prompt engineering and retrieval tweaks to return high-quality, citation-backed answers.
  • Handles all model management behind the scenes—no extra API keys or fine-tuning steps for you.
Developer Experience ( A P I & S D Ks)
  • Open-Source Foundation: NucliaDB (710+ GitHub stars, AGPLv3 license, Python/Rust) provides transparency into core retrieval mechanisms
  • Python SDK: pip install nuclia (Python 3.8+, ~21,000 weekly downloads) - full API coverage
  • JavaScript/TypeScript SDK: @nuclia/core (React, Next.js, Angular, Vue.js, Svelte support)
  • REST API: Regional endpoints https://{region}.rag.progress.cloud/api/v1/ with comprehensive documentation
  • Key Endpoints: /ask (generative answers), /find (semantic search), /upload (ingestion), /remi (quality evaluation)
  • Dual Documentation: docs.rag.progress.cloud (primary) + legacy docs.nuclia.dev (fragmentation concern)
  • RAG Cookbook: Downloadable comprehensive guide for developers
  • Code Example Simplicity: Upload and search in just a few Python lines with intuitive SDK design
  • API-First Design: Complete programmatic control over all platform capabilities
  • No open API or official SDKs—everything happens through the Pyx interface.
  • Embedding Pyx into other apps or calling it programmatically isn’t supported today.
  • Closed ecosystem: no GitHub examples or community plug-ins.
  • Great for teams wanting a turnkey tool, but it limits deep customization or dev-driven extensions.
  • Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat. API Documentation
  • Offers open-source SDKs—like the Python customgpt-client—plus Postman collections to speed integration. Open-Source SDK
  • Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
Performance & Accuracy
  • Benchmark Leader: Nuclia with OpenAI embeddings achieved highest scores vs Vectara on Docmatix 1.4k dataset across answer relevance, context relevance, correctness
  • 100M Vectors: Fully ingested and optimized in ~20 minutes with sufficient worker allocation
  • REMi v2 Speed: 30x faster inference than original Mistral-based implementation (Llama 3.2-3B based)
  • Four-Index Hybrid Search: Document Index (property filtering), Full Text (keyword/fuzzy), Vector/Chunk (semantic), Knowledge Graph (entity relationships)
  • Dynamic Sharding: Automatic shard creation as vector counts grow with index node replication for fault tolerance
  • Fast Deployment: 2-hour initial ingestion, 48-hour full deployment timeline
  • ACID Compliance: TiKV key-value store (Tier 2) manages resource metadata with transaction guarantees
  • Three-Tier Storage: Tier 3 (S3/GCS blobs), Tier 2 (TiKV metadata), Tier 1 (sharded indexes)
  • Aims to serve accurate, real-time answers from internal documents—though public benchmark data is sparse.
  • Likely competitive with standard GPT-based RAG systems on relevance and hallucination control.
  • No detailed info on anti-hallucination tactics or turbo re-ranking like CustomGPT touts.
  • Auto-sync keeps documents fresh, so retrieval context is always current.
  • Delivers sub-second replies with an optimized pipeline—efficient vector search, smart chunking, and caching.
  • Independent tests rate median answer accuracy at 5/5—outpacing many alternatives. Benchmark Results
  • Always cites sources so users can verify facts on the spot.
  • Maintains speed and accuracy even for massive knowledge bases with tens of millions of words.
Customization & Flexibility ( Behavior & Knowledge)
  • 30+ RAG Optimization Parameters: Fine-grained control over retrieval behavior
  • Custom Chunking Strategies: Configurable text segmentation for optimal context windows
  • Context Size Configuration: Adjust context sent to LLMs based on use case
  • Hybrid Search Weighting: Balance keyword vs semantic search relevance
  • Retrieval Agent Autonomy: Automatically select optimal strategies per query characteristics
  • Embedding Model Flexibility: Switch per Knowledge Box (Nuclia multilingual + OpenAI options)
  • Prompt Lab Experimentation: Test configurations with actual data before production deployment
  • LLM Provider Switching: Change models without architectural changes (7 providers supported)
  • Auto-sync keeps your knowledge base updated without manual uploads.
  • No persona or tone controls—the AI voice stays neutral and consistent.
  • Strong access controls let admins set who can see what, although deeper behavior tweaks aren’t available.
  • A closed, secure environment—great for content updates, limited for AI behavior tweaks or deployment variety.
  • Lets you add, remove, or tweak content on the fly—automatic re-indexing keeps everything current.
  • Shapes agent behavior through system prompts and sample Q&A, ensuring a consistent voice and focus. Learn How to Update Sources
  • Supports multiple agents per account, so different teams can have their own bots.
  • Balances hands-on control with smart defaults—no deep ML expertise required to get tailored behavior.
Pricing & Scalability
  • Fly Tier: $700/month - 10GB/15K resources, 750MB max file, 1 Knowledge Box, cloud only, 10K tokens/month
  • Growth Tier: $1,750/month - 50GB/80K resources, 1.5GB max file, 2 Knowledge Boxes, Prompt Lab, 10K tokens/month
  • Enterprise Tier: Custom pricing - Unlimited data/file size, 11 Knowledge Boxes, hybrid/on-prem deployment, 10K tokens/month
  • Token Consumption: $0.008/token beyond 10K/month included across all tiers
  • 14-Day Free Trial: Available without disclosed credit card requirement
  • AWS Marketplace: Simplifies enterprise procurement with existing cloud spend commitments
  • Competitive Entry Point: $700/month undercuts enterprise alternatives (Drift $30K+/year, Yellow.ai similar)
  • Scaling Consideration: Token-based consumption pricing requires careful usage forecasting for budget predictability
  • Uses a seat-based plan (~$30 per user per month).
  • Cost-effective for small teams, but can add up if everyone in the company needs access.
  • Document or token limits aren’t published—content may be “unlimited,” gated only by user seats.
  • Offers a free trial and enterprise deals; scaling is as simple as buying more seats.
  • Runs on straightforward subscriptions: Standard (~$99/mo), Premium (~$449/mo), and customizable Enterprise plans.
  • Gives generous limits—Standard covers up to 60 million words per bot, Premium up to 300 million—all at flat monthly rates. View Pricing
  • Handles scaling for you: the managed cloud infra auto-scales with demand, keeping things fast and available.
Security & Privacy
  • SOC2 Type 2 Certified: Annual audits for enterprise security assurance
  • ISO 27001 Certified: Annually audited information security management
  • 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
  • Tenant Isolation: Customer data separation ensures multi-tenant security
  • Audit Logs: Standard across all pricing tiers for compliance tracking
  • API Key Management: Temporal keys and rotation for security hygiene
  • CRITICAL: 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
  • Enterprise-grade privacy: each customer’s data is isolated and encrypted in transit and at rest.
  • Based in Germany, so GDPR compliance is implied; no data mixing between accounts.
  • Doesn’t train external LLMs on your data—queries stay private beyond internal indexing.
  • Role-based access is built-in, though on-prem deployment or detailed certifications aren’t publicly documented.
  • Protects data in transit with SSL/TLS and at rest with 256-bit AES encryption.
  • Holds SOC 2 Type II certification and complies with GDPR, so your data stays isolated and private. Security Certifications
  • Offers fine-grained access controls—RBAC, two-factor auth, and SSO integration—so only the right people get in.
Observability & Monitoring
  • REMi Real-Time Dashboard: Answer relevance, context relevance, groundedness, correctness (0-5 scale)
  • 7-Day Rolling Averages: Performance evolution graphs spanning 24 hours to 30 days
  • Health Displays: Quality metrics shown in real-time for immediate visibility
  • Four Quality Dimensions: Answer Relevance (query alignment), Context Relevance (passage quality), Groundedness (source derivation), Answer Correctness (ground truth alignment)
  • REMi v2 Performance: 30x faster inference (Llama 3.2-3B) vs original Mistral implementation
  • Benchmark Validation: Tested against Vectara on Docmatix 1.4k dataset with highest scores
  • Audit Logs: Standard across all tiers for compliance and security tracking
  • MISSING FEATURE: Proactive alerting not documented (monitoring exists, automated alerts unclear)
  • Admins get basic stats on user activity, query counts, and top-referenced documents.
  • No deep conversation analytics or real-time logging dashboards.
  • Useful for tracking adoption, but lighter on insights than solutions with full analytics suites.
  • Mostly “set it and forget it”—contact Pyx support if something seems off.
  • Comes with a real-time analytics dashboard tracking query volumes, token usage, and indexing status.
  • Lets you export logs and metrics via API to plug into third-party monitoring or BI tools. Analytics API
  • Provides detailed insights for troubleshooting and ongoing optimization.
Support & Ecosystem
  • Dual Documentation Portals: docs.rag.progress.cloud (primary) + legacy docs.nuclia.dev (fragmentation concern)
  • RAG Cookbook: Comprehensive downloadable guide for developers
  • SDK Ecosystem: Python (~21K weekly downloads) + JavaScript/TypeScript with active developer usage
  • 14-Day Free Trial: Hands-on evaluation without credit card requirement
  • Progress Enterprise Support: Backed by 2,000+ employee parent company infrastructure
  • AWS Marketplace: Available November 2025 for streamlined enterprise procurement
  • Open-Source Community: NucliaDB 710+ GitHub stars with AGPLv3 license transparency
  • API-First Support: Comprehensive REST API documentation with regional endpoints
  • Offers direct email, phone, and chat support, plus a hands-on onboarding approach.
  • No large open-source community or external plug-ins—it’s a closed solution.
  • Product updates come from Pyx’s own roadmap; user-built extensions aren’t part of the ecosystem.
  • Focuses on quick setup and minimal admin overhead for internal knowledge search.
  • Supplies rich docs, tutorials, cookbooks, and FAQs to get you started fast. Developer Docs
  • Offers quick email and in-app chat support—Premium and Enterprise plans add dedicated managers and faster SLAs. Enterprise Solutions
  • Benefits from an active user community plus integrations through Zapier and GitHub resources.
No- Code Interface & Usability
  • Target Users: Non-technical teams (marketing, HR, legal, customer support) with zero coding required
  • Visual Dashboard: Create Knowledge Box, upload documents, deploy search widget in single session
  • Point-and-Click Widget Editor: Configure suggestions, filters, metadata, thumbnails, answer modes visually
  • Pre-Built Ingestion Agents (Beta): Automated workflows for labeling, summarization, graph extraction, Q&A generation, content safety
  • Prompt Lab: Visual interface for side-by-side LLM testing with actual data
  • Role-Based Access Control: Visual permission management separating Account and Knowledge Box concerns
  • Rapid Deployment: Progress explicitly markets minutes-to-production capability for business users
  • Shadow DOM Architecture: Advanced users can apply CSS styling via cssPath attribute for customization
  • Presents a straightforward web/desktop UI: users log in, ask questions, and get answers—no coding needed.
  • Admins connect data sources through a no-code interface, and Pyx indexes them automatically.
  • Offers minimal customization controls on purpose—keeps the UI consistent and uncluttered.
  • Perfect for an internal Q&A hub, but not for external embedding or heavy brand customization.
  • Offers a wizard-style web dashboard so non-devs can upload content, brand the widget, and monitor performance.
  • Supports drag-and-drop uploads, visual theme editing, and in-browser chatbot testing. User Experience Review
  • Uses role-based access so business users and devs can collaborate smoothly.
R E Mi Evaluation Model ( Core Differentiator)
  • Proprietary Investment: Significant R&D differentiator addressing hallucination problem - absent from most competitors
  • REMi v2 (Current): Llama-REMi v1 based on Llama 3.2-3B with 30x faster inference vs original Mistral implementation
  • Continuous Quality Monitoring: Evaluates EVERY interaction across four dimensions (0-5 scale)
  • Answer Relevance: Measures how directly response addresses the query
  • Context Relevance: Assesses quality of retrieved passages relative to question
  • Groundedness: Evaluates degree to which answers derive from source context (hallucination detection)
  • Answer Correctness: Alignment with ground truth when available (optional dimension)
  • Benchmark Validation: Nuclia with OpenAI embeddings achieved highest scores vs Vectara on Docmatix 1.4k dataset across answer relevance, context relevance, correctness
  • Real-Time Visibility: Dashboard health displays with 7-day rolling averages and performance graphs (24h to 30d)
  • Competitive Advantage: Most RAG platforms lack continuous quality evaluation - Progress makes this core differentiator
N/A
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Open- Source Nuclia D B Foundation
  • GitHub Presence: 710+ stars, AGPLv3 license provides full transparency into core retrieval mechanisms
  • Technology Stack: Python and Rust implementation for performance and reliability
  • Managed Infrastructure: Progress removes operational burden while maintaining technical transparency
  • Three-Tier Storage: Tier 3 (S3/GCS blob storage), Tier 2 (TiKV key-value with ACID), Tier 1 (sharded indexes)
  • 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
  • Embedding Flexibility: Switchable per Knowledge Box (Nuclia multilingual + OpenAI options)
  • 100M Vector Performance: Full ingestion and optimization in ~20 minutes with sufficient worker allocation
  • Developer Trust: Open-source foundation allows code inspection and contribution vs black-box competitors
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Multi- Lingual Support
  • Nuclia Multilingual Embedding Model: Default model supporting multiple languages out-of-box
  • 60+ Document Format Processing: Multi-language content across PDF, Word, Excel, PPT, text, email
  • Automatic Transcription: Multi-language speech-to-text for audio/video content
  • Configurable Embeddings: Per Knowledge Box language optimization
  • LLM Provider Flexibility: 7 providers with varying multilingual capabilities (Claude, GPT, Gemini, Llama, etc.)
  • Global Customer Base: Deployed across Spain, US, international markets indicating production multilingual usage
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R A G-as-a- Service Assessment
  • Platform Type: TRUE RAG-AS-A-SERVICE PLATFORM - Core mission is retrieval-augmented generation backend with developer-first API access
  • Core Focus: Semantic search and generative Q&A across knowledge bases with transparent NucliaDB architecture
  • RAG Backend Design: Fully managed RAG infrastructure with embeddable widgets (NOT closed conversational marketing like Drift/Yellow.ai)
  • Programmatic Access: Complete REST API + dual SDKs (Python/JavaScript) for full knowledge base management
  • LLM Flexibility: 7 provider options switchable without architectural changes (Anthropic, OpenAI, Google, Meta, Cohere, Azure, Nuclia)
  • 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: NOT TRUE RAG-AS-A-SERVICE - Pyx AI is a standalone internal knowledge search application, not API-accessible RAG platform
  • Core Focus: Turnkey internal Q&A tool for employees - self-contained application vs developer-accessible RAG infrastructure
  • NO API Access: No REST API, SDKs, or programmatic access - fundamentally different from API-first RaaS platforms (CustomGPT, Vectara, Nuclia)
  • Closed Application: Users access via web/desktop interface only - cannot build custom applications on top or integrate with other systems
  • No Developer Features: No embedding endpoints, chunking configuration, retrieval customization, or model selection - opaque RAG implementation
  • Comparison Category Mismatch: Invalid comparison to RAG-as-a-Service platforms - more comparable to internal search tools (Glean, Guru, Notion AI)
  • SaaS vs RaaS: Software-as-a-Service (standalone app) NOT Retrieval-as-a-Service (API infrastructure for developers)
  • Best Comparison Category: Internal knowledge management tools (Glean, Guru), NOT developer RAG platforms (CustomGPT, Pinecone Assistant)
  • Use Case Fit: Small teams (<50 users) wanting simple employee knowledge search - not organizations building custom AI applications
  • No Extensibility: Cannot embed in websites, build chatbots, integrate with business systems - siloed internal tool only
  • GDPR Appeal: Germany-based with implicit compliance - suitable for European SMBs prioritizing data residency over platform capabilities
  • Platform Recommendation: Should be compared to internal search tools (Glean, Guru), not listed alongside RAG-as-a-Service platforms
  • Platform Type: TRUE RAG-AS-A-SERVICE PLATFORM - all-in-one managed solution combining developer APIs with no-code deployment capabilities
  • 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)
  • Pricing Advantage: $700/month entry undercuts enterprise competitors (Drift $30K+/year, Yellow.ai similar, CustomGPT varies)
  • REMi Differentiator: Proprietary continuous quality monitoring addresses hallucination problem - capability absent from most competitors
  • Benchmark Leadership: Achieved highest scores vs Vectara on Docmatix 1.4k dataset (answer relevance, context relevance, correctness)
  • Open-Source Trust: NucliaDB transparency (710+ GitHub stars) vs black-box competitors (Lindy.ai, Drift, Yellow.ai)
  • 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: Turnkey internal knowledge search tool (Germany-based) designed as standalone application for employee Q&A, not embeddable chatbot platform
  • Target customers: Small to mid-size European teams needing simple internal knowledge search, organizations prioritizing GDPR compliance and German data residency, and companies wanting no-fuss deployment without developer involvement
  • Key competitors: Glean, Guru, notion AI, and traditional enterprise search tools; less comparable to customer-facing chatbots like CustomGPT/Botsonic
  • Competitive advantages: Intentionally simple scope with minimal configuration overhead, auto-sync keeping knowledge base current without manual uploads, Germany-based with implicit GDPR compliance and EU data residency, seat-based pricing (~$30/user/month) clear and predictable, and strong access controls with role-based permissions for secure internal deployment
  • Pricing advantage: ~$30 per user per month seat-based pricing; cost-effective for small teams but can scale expensively for large organizations; simpler pricing than usage-based platforms but less economical for high user counts; best value for teams <50 users needing internal search only
  • Use case fit: Perfect for small European teams wanting simple internal knowledge Q&A without coding, organizations needing GDPR-compliant employee knowledge base with German data residency, and companies prioritizing quick setup over flexibility; not suitable for public-facing chatbots, API integrations, or heavy customization requirements
  • 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
  • Three-Tier Architecture: S3/GCS blob storage (Tier 3), TiKV metadata (Tier 2), sharded indexes (Tier 1)
  • 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
  • Embedding Flexibility: Configurable per Knowledge Box (Nuclia multilingual default + OpenAI embeddings)
  • Undisclosed LLM: Likely runs GPT-3.5 or GPT-4 under the hood but exact model not publicly documented
  • NO Model Selection: Cannot switch or choose between different LLMs - single model configuration for all queries
  • NO Model Toggles: No speed vs accuracy options - every query uses same model configuration
  • Opaque Architecture: Model details, context window size, and capabilities not exposed to users
  • Focus on Simplicity: Intentionally hides technical complexity - users ask questions, get answers
  • NO Fine-Tuning: Cannot customize or train model on specific domain data for specialized responses
  • Single RAG Engine: Less flexible than tools offering explicit GPT-3.5/GPT-4 choice or multi-model support
  • 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)
  • 30+ RAG Parameters: Custom chunking strategies, context size configuration, hybrid search weighting for fine-tuned optimization
  • REMi v2 Quality Monitoring: Continuous evaluation across Answer Relevance, Context Relevance, Groundedness, Correctness (30x faster inference)
  • Benchmark Leadership: Highest scores vs Vectara on Docmatix 1.4k dataset (answer relevance, context relevance, correctness)
  • Pre-Built Ingestion Agents (Beta): Labeler (auto-classification), Generator (summaries/JSON), Graph Extraction (entities/relationships), Q&A Generator, Content Safety
  • Multimodal Processing: OCR for scanned documents/images, automatic speech-to-text for audio (MP3, WAV, AIFF), video transcript extraction
  • 60+ Document Formats: PDF, Word, Excel, PowerPoint, plain text, email formats with automatic parsing
  • Open-Source Foundation: NucliaDB (710+ GitHub stars, AGPLv3) provides transparency into retrieval mechanisms vs black-box platforms
  • Basic RAG Implementation: Conversational search over enterprise documents with context-aware follow-up questions
  • Auto-Sync: Connected file repositories automatically sync - document changes reflected almost instantly
  • Document Formats: Supports PDF, DOCX, PPT, TXT and more common enterprise formats
  • NO Advanced Controls: No chunking parameters, embedding model selection, or similarity threshold configuration exposed
  • NO Anti-Hallucination Metrics: No detailed transparency on citation attribution or confidence scoring mechanisms
  • NO Re-Ranking: No advanced re-ranking or turbo retrieval options mentioned
  • Closed System: RAG engine optimized for internal Q&A - limited visibility into underlying retrieval architecture
  • Competitive Performance: Likely competitive with standard GPT-based RAG for relevance but lacks published benchmarks
  • Core architecture: GPT-4 combined with Retrieval-Augmented Generation (RAG) technology, outperforming OpenAI in RAG benchmarks RAG Performance
  • Anti-hallucination technology: Advanced mechanisms reduce hallucinations and ensure responses are grounded in provided content Benchmark Details
  • Automatic citations: Each response includes clickable citations pointing to original source documents for transparency and verification
  • Optimized pipeline: Efficient vector search, smart chunking, and caching for sub-second reply times
  • Scalability: Maintains speed and accuracy for massive knowledge bases with tens of millions of words
  • Context-aware conversations: Multi-turn conversations with persistent history and comprehensive conversation management
  • Source verification: Always cites sources so users can verify facts on the spot
Use Cases
  • Enterprise Knowledge Management: Non-technical teams (marketing, HR, legal, customer support) deploying knowledge bases in minutes
  • Healthcare & Pharma: Althaia Hospitals medical protocol search for 5,000+ healthcare professionals with HIPAA-grade security needs
  • Financial Services: BrokerChooser replaced keyword search with generative AI for significant conversion increases
  • Education: Columbia Business School and Barry University for academic knowledge discovery and institutional knowledge management
  • Engineering & Research: NAFEMS knowledge discovery across thousands of technical publications for international membership
  • Trade Organizations: CCOO (Spain's largest union) serving 1M+ members with knowledge retrieval platform
  • Intelligent Document Processing: Automatic document classification, routing, extraction, risk identification, and summary generation
  • 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
  • Internal Knowledge Search: Primary use case - employees asking questions about company documents and policies
  • Document Q&A: Quick answers from internal documentation without manual searching through files
  • Team Onboarding: New employees finding information in knowledge base without bothering colleagues
  • Policy & Procedure Lookup: HR, compliance, and operational procedure retrieval for staff
  • Small European Teams: GDPR-compliant internal search for EU organizations prioritizing data residency
  • No-Code Deployment: Non-technical teams wanting simple setup without developer involvement
  • NOT SUITABLE FOR: Public-facing chatbots, customer support, API integrations, multi-channel deployment, or heavy customization requirements
  • 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)
  • Financial services: Product guides, compliance documentation, customer education with GDPR compliance
  • 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
  • GDPR Compliance: Germany-based with implicit EU data protection compliance
  • German Data Residency: EU data storage location for organizations requiring regional data sovereignty
  • Enterprise Privacy: Each customer's data isolated and encrypted in transit and at rest
  • NO Model Training: Customer data not used to train external LLMs - queries stay private beyond internal indexing
  • Role-Based Access: Built-in access controls - admins set who can see what documents
  • NO Cross-Account Data: Data never mixed between customers - strict tenant isolation
  • Limited Certifications: On-prem deployment or detailed security certifications (SOC 2, ISO 27001) not publicly documented
  • NO HIPAA Certification: Not documented for healthcare PHI processing - not suitable for regulated medical data
  • Best For: European SMBs needing GDPR compliance without enterprise certification requirements
  • 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
  • Growth Tier: $1,750/month - 50GB/80K resources, 1.5GB max file, 2 Knowledge Boxes, Prompt Lab access, 10K tokens/month
  • Enterprise Tier: Custom pricing - Unlimited data/file size, 11 Knowledge Boxes, hybrid/on-prem deployment, 10K tokens/month
  • Token Consumption: $0.008/token beyond 10K/month included across all tiers for usage-based scaling
  • 14-Day Free Trial: Available without disclosed credit card requirement for hands-on evaluation
  • AWS Marketplace: Available November 2025 for simplified enterprise procurement with existing cloud spend commitments
  • Competitive Entry Point: $700/month undercuts enterprise alternatives (Drift $30K+/year, Yellow.ai similar, LiveChat per-agent scaling)
  • 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
  • Seat-Based Pricing: ~$30 per user per month
  • Cost-Effective for Small Teams: Affordable for teams under 50 users with predictable monthly costs
  • Scalability Challenge: Can become expensive for large organizations (100 users = $3,000/month)
  • NO Published Document Limits: Content may be "unlimited" - gated only by user seats rather than storage caps
  • Free Trial Available: Hands-on evaluation before committing to paid plan
  • Enterprise Deals: Custom pricing available for larger deployments with volume discounts
  • Simple Scaling: Add more seats as team grows - no complex usage-based billing
  • Best Value For: Small European teams (<50 users) needing predictable costs vs token/usage-based platforms
  • 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
Support & Documentation
  • Dual Documentation Portals: docs.rag.progress.cloud (primary) + legacy docs.nuclia.dev (fragmentation concern during transition)
  • RAG Cookbook: Comprehensive downloadable guide for developers with implementation patterns and best practices
  • SDK Ecosystem: Python (~21K weekly downloads via pip install nuclia) + JavaScript/TypeScript (@nuclia/core on NPM)
  • REST API: Regional endpoints https://{region}.rag.progress.cloud/api/v1/ with complete programmatic control
  • Key Endpoints: /ask (generative answers), /find (semantic search), /upload (ingestion), /remi (quality evaluation)
  • 14-Day Free Trial: Hands-on evaluation platform without credit card requirement
  • Progress Enterprise Support: Backed by 2,000+ employee parent company infrastructure with dedicated account management
  • Open-Source Community: NucliaDB 710+ GitHub stars with AGPLv3 license transparency and community contributions
  • Integration Examples: WordPress, Strapi plugins, Pipedream official app, Zapier API-compatible, Chrome extension for web indexing
  • Progress Ecosystem: OpenEdge database connector, Sitefinity CMS integration ("first Generative CMS") for distribution advantages
  • Direct Support: Email, phone, and chat support with hands-on onboarding approach
  • User-Friendly Setup: Minimal admin overhead - connect data sources and employees start asking questions
  • NO Open-Source Community: Closed solution without external plug-ins or user-built extensions
  • NO Public API: No developer documentation or programmatic access for custom integrations
  • Product Roadmap: Updates come from Pyx's own roadmap - no user-contributed features or marketplace
  • Quick Deployment: Emphasizes fast setup and minimal configuration vs complex enterprise platforms
  • Limited Technical Depth: Support focused on basic usage - not extensive developer or API documentation
  • Best For: Non-technical teams wanting simple, reliable support without complex integration needs
  • Documentation hub: Rich docs, tutorials, cookbooks, FAQs, API references for rapid onboarding Developer Docs
  • Email and in-app support: Quick support via email and in-app chat for all users
  • Premium support: Premium and Enterprise plans include dedicated account managers and faster SLAs
  • Code samples: Cookbooks, step-by-step guides, and examples for every skill level API Documentation
  • Open-source resources: Python SDK (customgpt-client), Postman collections, GitHub integrations Open-Source SDK
  • 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
  • Token-Based Billing Complexity: $0.008/token beyond 10K/month requires careful usage forecasting vs predictable seat-based pricing
  • 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 Public API: Cannot embed Pyx into other apps or call it programmatically - standalone UI only
  • NO Embedding Options: Not designed for website widgets, Slack bots, or public-facing deployment
  • NO Messaging Integrations: No Slack, Teams, WhatsApp, or other chat platform connectors
  • Limited Branding: Minimal customization (logo/colors) - designed as internal tool, not white-label solution
  • Siloed Platform: Standalone interface rather than extensible platform - no plug-ins or marketplace
  • NO Advanced Controls: Cannot configure RAG parameters, model selection, or retrieval strategies
  • NO Analytics Dashboard: Lighter on insights than solutions with full conversation analytics suites
  • Seat-Based Cost Scaling: Becomes expensive for large organizations vs usage-based or project-based pricing
  • Limited to Internal Use: Not suitable for customer-facing chatbots, developer-heavy customization, or API integrations
  • Best For: Small European teams (<50 users) prioritizing simplicity and GDPR compliance over flexibility and features
  • 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

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Final Thoughts

Final Verdict: Progress Agentic RAG vs Pyx

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

  • You value very quick setup (30-60 minutes)
  • No manual data imports required
  • Excellent ease of use with conversational interface

Best For: Very quick setup (30-60 minutes)

Migration & Switching Considerations

Switching between Progress Agentic RAG and Pyx 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 Pyx begins at $30/month. Total cost of ownership should factor in implementation time, training requirements, API usage fees, and ongoing support. Enterprise deployments typically see annual costs ranging from $10,000 to $500,000+ depending on scale and requirements.

Our Recommendation Process

  1. Start with a free trial - Both platforms offer trial periods to test with your actual data
  2. Define success metrics - Response accuracy, latency, user satisfaction, cost per query
  3. Test with real use cases - Don't rely on generic demos; use your production data
  4. Evaluate total cost - Factor in implementation time, training, and ongoing maintenance
  5. Check vendor stability - Review roadmap transparency, update frequency, and support quality

For most organizations, the decision between Progress Agentic RAG and Pyx 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.

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

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Priyansh Khodiyar's avatar

Priyansh Khodiyar

DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.

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