In this comprehensive guide, we compare BotsCrew and Progress Agentic RAG 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 BotsCrew and Progress Agentic RAG, 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 BotsCrew if: you value fortune 500-proven expertise: samsung next, honda, mars, adidas, virgin, bmc software clients
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
About BotsCrew
BotsCrew is enterprise chatbot development services with custom ai solutions. Enterprise chatbot development services company with custom AI solutions, not self-service RAG platform. Founded 2016, acquired by CourtAvenue (Feb 2025). Serves Fortune 500 with white-glove development starting at $600/month + $3,000+ setup costs. Founded in 2016, headquartered in London, UK / Lviv, Ukraine, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
88/100
Starting Price
$600/mo
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
Key Differences at a Glance
In terms of user ratings, BotsCrew in overall satisfaction. From a cost perspective, BotsCrew starts at a lower price point. The platforms also differ in their primary focus: Chatbot Platform versus Enterprise Software. 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
BotsCrew
Progress Agentic RAG
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Supported Formats: 100+ document file types for knowledge base building (PDFs, websites, help center content, plain text)
Scale Proven: Kravet deployment processed 125,000 product pages + 1,000+ static files across various formats
NoForm.ai: Website content learning from single URL 'almost immediately' - chatbot learns 'almost everything about our company' from website link
Knowledge Updates: Manual uploads required - no automatic cloud syncing or retraining from connected sources
Missing Cloud Integrations: No Google Drive, Dropbox, or Notion automatic syncing - significant gap vs modern RAG platforms
Content Management: Updates flow through platform's content management system with manual intervention required
API Limitation: No programmatic document upload or knowledge base management via API
Enterprise Proven: FIBA Basketball World Cup chatbot handled 72,000 conversations during tournament
Critical Gap: Knowledge ingestion requires UI-based uploads or professional services engagement vs self-service API access
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)
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
Messaging Platforms: Facebook Messenger (primary channel), WhatsApp Business API, Instagram, Telegram (G2 verified), SMS via Plivo integration
Enterprise Channels: Slack deployments, website widget via copy-paste code snippet added before </body> tag
Microsoft Teams: Blog content exists but native support unconfirmed - unclear if production-ready
CRM Integrations: Salesforce, HubSpot, Zendesk Suite for lead capture and case management
Enterprise Systems: Google Workspace, Slack, Shopify, PayPal, SAP (e-commerce implementations)
Zapier: NOT natively confirmed - integration approach emphasizes custom development services vs pre-built marketplace connectors
Webhooks: Availability implied but not explicitly documented for self-service use
Unified Inbox: Manages all channel conversations from single interface with full context preservation
Integration Model: 'Connect your bot with any software you use' through development services rather than self-service APIs
Multi-Lingual: 100+ languages supported with verified deployment operating simultaneously in English, French, German, Dutch, Polish, Turkish, Arabic (WhatsApp implementation)
Conversation History: Single inbox preserves full context across all channels and conversation turns
Dialog & User Journey Management: Not just messages with buttons - manage complex conversations using decision trees to ensure smooth and engaging dialogue with intent recognition capabilities
Analytics: Advanced performance tracking including goal completion rates, fallback rates, user satisfaction scores, revenue attribution
Human Handoff: Seamless live chat transfer with full conversation transcript passed to agents - documented Freshchat integration
Context Management: Context-aware multi-turn dialogue management across conversation sessions with personalized responses based on previous interactions and customer data
Conversation Quality: Target accuracy rate 80%+ with real-time monitoring and quality tracking
Side-by-Side Testing: Compare responses across models using actual data in Prompt Lab
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)
Critical Distinction: BotsCrew does NOT provide a public RAG API - fundamentally NOT a developer-first platform
Misleading Claim: 'RAG API: Yes - extensive integration with any open API' means platform can consume external APIs, NOT expose RAG capabilities through APIs
Available API (common.botscrew.net): Limited utility API for chatbot flow operations only - datetime formatting, math calculations, string operations, email sending, user redirect
NOT a RAG API: Cannot create agents, upload knowledge, query knowledge base, or access embeddings/vector store via API
Java SDK Only: Spring Boot framework (bot-framework-core, bot-framework-nlp, bot-framework-messenger) - last updated February 2020 (4+ years outdated)
No Python SDK: Major limitation for data science teams and backend developers
No JavaScript SDK: Blocks modern web development workflows
Documentation Quality: Basic with no developer portal, cookbook examples, or RAG-specific guides comparable to developer-first platforms
GitHub Activity: Open-source Java framework exists but last commit February 2020 - effectively abandoned
Use Case Mismatch: Cannot use BotsCrew as RAG backend for self-service development - requires professional services engagement
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
Primary Advantage: Fortune 500-proven enterprise chatbot development services with comprehensive white-label program and full-cycle expertise
White-Label Leadership: Zero-commission reselling, complete brand removal, custom domains/dashboards - one of market's best partner programs
Enterprise Credentials: HIPAA with BAA, GDPR, SOC 2, ISO 27001 compliance enables regulated industry adoption
Professional Services Depth: 8+ years experience, conversational design team, 14-day pilot program, post-delivery support beyond scope
CourtAvenue Backing: February 2025 acquisition provides US market access and enterprise resources
Primary Challenge: NOT a RAG-as-a-Service platform - cannot compare directly to CustomGPT.ai or developer-first RAG APIs
Developer Friction: No RAG API, no knowledge upload API, no Python/JS SDKs, outdated Java framework (2020)
Pricing Barrier: $600/month + $3,000+ setup + $50-99/hour services + $10,000 minimum vs competitors with sub-$100 self-service tiers
Time-to-Value: 2+ weeks implementation vs minutes for self-service platforms - 'not a platform where you can build chatbot in couple of hours'
Market Position: Competes with enterprise chatbot development agencies (IBM Watson consultants, Accenture) vs RAG API platforms (CustomGPT.ai, Pinecone Assistant)
Use Case Fit: Exceptional for enterprises seeking fully managed custom chatbot development; poor fit for developers seeking self-service RAG APIs
Comparison Warning: Direct feature comparison with RAG-as-a-Service platforms is fundamentally misleading due to different business models and architectures
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: 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
A I Models
OpenAI Models: GPT-4, GPT-4o, GPT-4.5 documented and supported for production deployments
Anthropic Claude: Claude 3 Opus integration available for enterprise applications
Open Source LLMs: Llama 3 support for cost optimization and on-premise deployment flexibility
Hybrid NLU: DialogFlow integration via SDK for combined traditional NLU + LLM approaches
Legacy Compatibility: LUIS, Rasa.ai support for existing enterprise infrastructure
Vector Database: Pinecone integration for enterprise-scale RAG deployments and vector search
Selective LLM Usage: "Build chatbot with DialogFlow and add GPT only to certain parts of conversation flow" - cost/performance optimization strategy
Professional Services Model: Model selection NOT self-service - determined during discovery phase with BotsCrew development team
No Automatic Routing: No dynamic model switching or automatic model selection capabilities available
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
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
Documented Accuracy Improvement: Kravet Inc. case study shows AI answer accuracy improved from under 60% to approximately 90% through professional optimization
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 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)
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
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
High-Touch Support: Phone and email support with dedicated project management attention
Dedicated Project Management: Weekly meetings, backlog system, continuous engagement throughout project lifecycle and beyond
Post-Delivery Support: Assistance continuing beyond project scope and original engagement (BMC Software testimonial: "helpful and responsive, continuing to assist us post-delivery")
Training Resources: Documentation, webinars, and in-person training available for enterprise clients
Blog Content: Extensive technical content at botscrew.com/blog covering RAG, LLM evaluation, enterprise deployment best practices
AI Newsletter: Bi-weekly newsletter with 1,000+ readers from Google, Meta, Amazon for industry insights
No Community Forum: Limited peer-to-peer support resources - relies on professional services model for all support
Open-Source Framework: Java bot framework on GitHub (bot-framework-core, bot-framework-nlp, bot-framework-messenger) last updated February 2020
Awards Recognition: Top AI Chatbot Development Company 2024 (Clutch), Clutch Champion 2023, #1 AI Developer worldwide 2017
Service Level Agreement: SLA available as part of comprehensive enterprise chatbot services package
Active community: User community plus 5,000+ app integrations through Zapier ecosystem
Regular updates: Platform stays current with ongoing GPT and retrieval improvements automatically
Additional Considerations
Proven Flexibility: Platform is very flexible with the ability to add custom integrations and features if needed through professional services engagement
Multilingual Strength: Native integrations for FB Messenger and website widgets with on-demand connections to WhatsApp, Twitter, Telegram - bot lives on multiple platforms without duplication
Learning Curve: At first look everything can seem very complicated for new users, requiring time investment beyond quick setup expectations
Time Investment Required: Not a platform where you can build a chatbot in couple of hours and immediately test - users should be prepared to spend more time though the result pays off
Helpful Support Team: BotsCrew team very helpful, providing guidance and assistance throughout the whole process with post-delivery support beyond scope
Intuitive Once Learned: After initial complexity, platform becomes very intuitive and easy to use for quickly setting up and connecting chatbots on websites
Cost Consideration: Product is on the more expensive side with $600/month platform + $3,000+ setup + $50-99/hour services positioning it as enterprise solution
Premium Positioning: Really more of an enterprise solution with Fortune 500 clients (Samsung NEXT, Honda, Mars, Adidas, Virgin) vs SMB-focused platforms
Limited AI Intuitiveness: Chatbot not as intuitively driven by artificial intelligence with conversations predefined based on pre-written scripts requiring manual setup
No Mobile App: No mobile application available which would be great addition for on-the-go management
Best Fit: Enterprises with $10,000+ budgets seeking fully managed custom chatbot development with white-label reselling opportunities
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
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.
Limitations & Considerations
NOT a Self-Service Platform: Custom development services company vs self-service SaaS - fundamentally different product category
No RAG API: Cannot create agents, upload knowledge, query knowledge base, or access embeddings via API programmatically
Misleading API Claims: "RAG API: Yes" means platform consumes external APIs, NOT expose RAG capabilities through developer APIs
Outdated SDK: Java SDK only (Spring Boot framework) last updated February 2020 (4+ years outdated), effectively abandoned on GitHub
No Python/JavaScript SDKs: Major limitation blocks data science teams and modern web development workflows
Manual Knowledge Updates: No automatic cloud syncing or retraining - requires UI-based uploads or professional services engagement
Missing Cloud Integrations: No Google Drive, Dropbox, Notion automatic syncing - significant gap vs modern RAG platforms
No API for Content Management: No programmatic document upload or knowledge base management capabilities
Requires Professional Services: Advanced features and enterprise deployments need development team engagement vs self-service configuration
Long Implementation Time: 2+ weeks minimum for highly customized solutions - "not a platform where you can build chatbot in couple of hours"
High Cost Barrier: $600/mo + $3,000 setup + $50-99/hr + $10,000 minimum vs $99/mo self-service competitors
Use Case Mismatch: Cannot use BotsCrew as RAG backend for self-service development - requires professional services for all implementations
Limited Documentation Quality: Basic with no developer portal, cookbook examples, or RAG-specific guides comparable to developer-first platforms
Comparison Warning: Architectural comparison to CustomGPT.ai fundamentally misleading - different business models, target customers, delivery methods
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
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
Core Agent Features
N/A
Retrieval Agents: Autonomously select optimal retrieval strategies based on query characteristics
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)
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
R E Mi Evaluation Model ( Core Differentiator)
N/A
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
Open- Source Nuclia D B Foundation
N/A
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
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
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
Customer Base & Case Studies
N/A
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
After analyzing features, pricing, performance, and user feedback, both BotsCrew and Progress Agentic RAG are capable platforms that serve different market segments and use cases effectively.
When to Choose BotsCrew
You value fortune 500-proven expertise: samsung next, honda, mars, adidas, virgin, bmc software clients
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
Migration & Switching Considerations
Switching between BotsCrew and Progress Agentic RAG 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
BotsCrew starts at $600/month, while Progress Agentic RAG begins at $700/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
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 BotsCrew and Progress Agentic RAG 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 13, 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.
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