In this comprehensive guide, we compare Deviniti and LiveChat 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 Deviniti and LiveChat, 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 Deviniti if: you value strong compliance and security focus
Choose LiveChat if: you value mature 20+ year platform with proven enterprise reliability (adobe, paypal, ikea, samsung, best buy)
About Deviniti
Deviniti is self-hosted genai solutions for compliance-critical industries. Deviniti is an AI development company specializing in secure, self-hosted AI agents and LLM solutions for highly regulated industries like finance, healthcare, and legal, with expertise in RAG architecture and custom AI development. Founded in 2010, headquartered in Kraków, Poland, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
77/100
Starting Price
Custom
About LiveChat
LiveChat is enterprise live chat platform with ai-augmented customer support workflows. Mature 20+ year live chat platform owned by publicly-traded Text S.A. (WSE: TXT, $88.9M annual revenue) serving 37,000+ businesses including Adobe, PayPal, IKEA. NOT a RAG-as-a-Service platform—operates as human-agent live chat with AI augmentation features. Proprietary AI engine (not LLM model selection), limited knowledge sources (PDFs/websites only), no vector database controls, no anti-hallucination mechanisms. Strong for traditional customer support workflows. $20-$59/agent/month + $52/month ChatBot addon. Founded in 2002, headquartered in Wroclaw, Poland, the platform has established itself as a reliable solution in the RAG space.
Overall Rating
86/100
Starting Price
$20/mo
Key Differences at a Glance
In terms of user ratings, LiveChat in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: AI Development versus Customer Support. 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
Deviniti
LiveChat
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Builds custom pipelines to pull in pretty much any source—internal docs, FAQs, websites, databases, even proprietary APIs.
Works with all the usual suspects (PDF, DOCX, etc.) and can tap uncommon sources if the project needs it.
Project case study
Designs scalable setups—hardware, storage, indexing—to handle huge data sets and keep everything fresh with automated pipelines.
Learn more
Supported formats: PDFs and website crawling only (max 2,000 pages per website source)
Plan-based limits: Team (10 files / 3 websites), Business (30 files / 10 websites), Enterprise (custom limits)
Automatic retraining: Configurable intervals for knowledge base updates
CRITICAL LIMITATION: No NO support for DOCX, TXT, CSV, Excel, audio, video, code files (limited to PDFs/websites vs 1,400+ formats in RAG platforms)
CRITICAL LIMITATION: No NO cloud storage integrations (Google Drive, Dropbox, OneDrive, Notion, Confluence) for native sync - manual uploads only
Architecture gap: Designed for customer service knowledge bases, not sophisticated document retrieval - no chunking parameters, embedding models, or vector database configurations exposed
Scaling concerns: Maximum 2,000 pages per website source and hard limits on total sources per plan quickly exceed enterprise-scale document corpus requirements
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
Plugs the chatbot into any channel you need—web, mobile, Slack, Teams, or even legacy apps—tailored to your stack.
Spins up custom API endpoints or webhooks to hook into CRMs, ERPs, or ITSM tools (dev work included).
Integration approach
Messaging platforms: Website chat widget, Facebook Messenger, WhatsApp Business API, Apple Messages for Business, Telegram, SMS (via 2way integration), email ticketing
Builds a domain-tuned AI chatbot with multi-turn memory, context, and any language you need (local LLMs included).
Can add lead capture, human handoff, and tight workflow hooks (e.g., IT tickets) exactly as you specify.
Case study
AI Reply Suggestions: Knowledge base-powered response recommendations for human agents based on conversation context - enhances agent productivity rather than replacing human interaction
Text Copilot: AI assistant helping agents navigate LiveChat platform efficiently with suggested responses, actions, and workflow guidance
Text Enhancement: Grammar correction and tone polishing for agent messages before sending - ensures professional communication quality
Tag Suggestions: Automatic conversation categorization and tagging for organization and reporting without manual classification effort
AI Summaries: Conversation summarization for agent handoffs and context transfer - reduces ramp-up time when conversations transfer between team members
AI Insights: Analyzes 1,000+ customer queries in 30 seconds to identify trends and patterns - enables data-driven support strategy optimization
Human-Agent Focus Philosophy: AI features designed to augment agent productivity, not replace human interaction - maintains human touch in customer conversations
ChatBot.com Separate Product: Traditional chatbot automation requires $52/month additional purchase using proprietary NLP engine (explicitly doesn't rely on Google Bard, OpenAI, or Bing AI)
CRITICAL LIMITATION - NO Anti-Hallucination Controls: Responses cannot be traced to source documents with citations - no citation attribution, source verification, or confidence scoring vs RAG platforms
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.
Customization & Branding
Everything’s bespoke: UI, tone, flows—whatever matches your brand.
Slots into your existing tools with custom styling and domain-specific dialogs—changes just take dev effort.
Custom approach
UI customization: Visual live editor with theme presets, color pickers supporting custom hex codes, logo uploads, position controls for widget placement on website
Branding control: Light/dark mode built-in theme switching with user preference detection, custom CSS for advanced styling beyond presets, logo and color scheme customization
White-labeling: Complete removal of LiveChat branding available on Enterprise plan only (custom pricing, minimum 5 seats); lower tiers (Starter/Team/Business) display LiveChat branding on widgets
Custom domain: Not explicitly documented in public materials; likely requires Enterprise plan with custom deployment infrastructure (specifics require sales engagement)
Design flexibility: Separate mobile widget settings with device-specific hiding options, WCAG 2.1 AA accessibility compliance with screen reader and keyboard navigation support, domain restrictions for trusted domains configuration
Mobile customization: Responsive widget with mobile-specific settings; mobile app customization separate from web widget (mobile app functionality limitations noted in user reviews)
Role-based access: Owner, Admin, and Agent roles with configurable permissions; agent groups for departmental routing enabling organizational structure within platform
LIMITATION: Enterprise-only white-labeling creates significant barrier for mid-market companies requiring brand removal without enterprise contract minimums
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
Pick any model—GPT-4, Claude, Llama 2, Falcon—whatever fits your needs.
Fine-tune on proprietary data for insider terminology, but swapping models means a new build/deploy cycle.
Our services
CRITICAL LIMITATION: No NO LLM model selection available - proprietary AI engine only
Architecture: ChatBot.com uses internal NLP system, explicitly doesn't rely on Google Bard, OpenAI, or Bing AI
Opaque processing: Model architecture, training data, capabilities not publicly documented
NO model routing: No Cannot choose between GPT-3.5, GPT-4, Claude, Gemini, or custom models based on query complexity or cost optimization
NO BYOLLM: No No bring-your-own-model capabilities for enterprise customization or fine-tuning
Competitive gap: This eliminates flexibility entirely vs RAG platforms offering multiple LLM providers and model selection (rated 3/10 for model flexibility - major limitation)
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)
Delivers a project-specific API—JSON over HTTP—made exactly for your endpoints.
Docs, samples, and support come straight from Deviniti engineers, not a public SDK.
Project example
Agent Chat API v3.5: REST and WebSocket (RTM) transports with OAuth 2.1 PKCE and Personal Access Tokens
JavaScript/Node.js SDK: @livechat/chat-sdk for agent operations with initialization and event handling
iOS SDK: Swift-based for iOS 15.6+ with CocoaPods, Carthage, and Swift Package Manager support
Android SDK: Kotlin-based SDK distributed via Gradle for native Android integration
Customer SDK: @livechat/customer-sdk for custom widget development and branded experiences
Documentation quality: Comprehensive for chat APIs with Postman collections, video tutorials, Discord community - genuinely strong investment in developer resources
Rate limits: 180 requests/minute per API key (may constrain high-volume applications)
CRITICAL LIMITATION: No NO Python SDK - JavaScript/Node.js/mobile only, limiting backend integration options for Python-based systems
CRITICAL LIMITATION: No NO RAG-specific APIs for semantic search, retrieval configuration, embedding management - APIs serve chat operations only
Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat.
API Documentation
Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
Performance & Accuracy
Uses best-practice retrieval (multi-index, tuned prompts) to serve precise answers.
Fine-tunes on your data to squash hallucinations, though perfecting it may need ongoing tweaks.
Our approach
Response time: Real-time chat delivery optimized for sub-second message delivery between agents and customers; server response times not publicly disclosed but consistently praised for reliability in G2/Capterra reviews
Accuracy metrics: No published accuracy benchmarks or AI performance metrics; platform focuses on operational metrics (queue times, agent response times, customer satisfaction) rather than AI retrieval accuracy
Context retrieval: AI Reply Suggestions retrieves responses from knowledge base sources based on conversation context; no configurable similarity thresholds, hybrid search, or retrieval optimization parameters exposed to users
Scalability: 37,000+ businesses served globally over 20+ years with enterprise customers (Adobe, PayPal, IKEA, Samsung); infrastructure supports high-volume chat operations but per-agent pricing model constrains cost scaling vs per-project pricing
Reliability: Enterprise SLA available on custom contracts with guaranteed response times and uptime commitments; platform stability consistently praised in reviews (4.5/5 G2, 4.6/5 Capterra) with "reliable platform" as common theme
Benchmarks: No published performance benchmarks comparing AI response accuracy, retrieval speed, or hallucination rates against competitors; platform designed for agent workflows rather than autonomous AI performance
Quality indicators: G2 rating 4.5/5 (761 reviews, 68% five-star ratings), Capterra 4.6/5 (1,700+ reviews); users praise reliability and ease of implementation, criticize rising prices and per-agent cost at scale
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.
Total control: add new sources with custom pipelines, tweak bot tone, inject live API calls—whatever you dream up.
Everything’s bespoke, so updates usually involve a quick dev sprint.
Case details
Knowledge Base Processing: Proprietary internal system processes PDFs and website crawls (max 2,000 pages, 10-30 files per plan tier) with automatic Q&A pair extraction
Automatic Retraining: Configurable intervals for knowledge base updates ensuring AI suggestions stay current with latest information
Widget Customization: Live editor with theme presets, color pickers supporting custom hex codes, logo uploads, position controls (desktop and mobile-specific settings)
Custom CSS Support: Advanced styling capabilities for design control beyond visual editor presets - full CSS customization available for matching brand guidelines
WCAG 2.1 AA Compliance: Accessibility support with screen readers and keyboard navigation ensuring inclusive user experiences
Domain Restrictions: Control which websites can embed widget through trusted domains configuration for security and access management
White-Labeling (Enterprise Only): Complete branding removal requires Enterprise plan (custom pricing, minimum 5 seats) - not available on Starter/Team/Business tiers
Role-Based Access: Owner, Admin, and Agent roles with configurable permissions; agent groups for departmental routing enabling organizational structure within platform
CRITICAL LIMITATION - Opaque Knowledge Processing: Methodology not publicly documented - no transparency into Q&A extraction algorithms, chunking strategies, or retrieval mechanisms
CRITICAL LIMITATION - NO Programmatic Knowledge Management: All knowledge base management requires UI interaction - no API for document upload, Q&A pair management, or automated knowledge updates
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
Project-based pricing plus optional maintenance—great for unique enterprise needs.
Your infra (cloud or on-prem) handles the load; the solution is built to scale to millions of queries.
Client portfolio
ChatBot addon: $52/month additional for automation (separate product purchase required)
Scaling cost example: 10-agent Business team with ChatBot = $642/month ($59×10 + $52) vs per-project pricing in RAG platforms
CONCERN: Note: Per-agent pricing escalates at scale - criticized in reviews as "rising prices" and "cost structure at scale" issue (vs token/project-based pricing in RAG competitors)
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
Deploy on-prem or private cloud for full data control and compliance peace of mind.
Uses strong encryption, access controls, and hooks into your existing security stack.
Security details
GDPR: Compliant with EU data residency option (Poland-based Text S.A.)
HIPAA: Compliant with BAA (Business Associate Agreement) on Enterprise plan
ISO 27001: Compliant (information security management)
PCI DSS: Compliant with built-in credit card masking for PII/PCI protection
FedRAMP: Compliant (federal government cloud security)
CSA Star Level 1: Compliant (Cloud Security Alliance certification)
AI data privacy: Customer data never used for LLM training, third-party AI partners (including OpenAI integrations) operate under zero-retention policies
Data isolation: Customer data never mixed across accounts, regional data center selection (America/Europe)
Audit logs: Available on Enterprise plans for security compliance
Encryption: TLS for transit, AES-256 at rest
LIMITATION: Note: SSO/SAML Enterprise-only - significant gap for mid-market companies with identity management requirements (Okta, OneLogin, Auth0, custom SAML requires highest tier)
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
Custom monitoring ties into tools like CloudWatch or Prometheus to track everything.
Can add an admin dashboard or SIEM feeds for real-time analytics and alerts.
More info
Benchmark comparisons: Industry average comparisons add competitive context to performance metrics
Scheduled reports: Daily/weekly/monthly delivery via email with CSV export for custom analysis
Staffing predictions (Business+): AI-powered scheduling optimization based on historical patterns
Google Analytics integration: Conversion tracking and customer journey analysis
Conversation logs: Full searchable archives with tag-based organization and filtering
LIMITATION: No NO AI performance metrics - no retrieval accuracy dashboards, semantic search performance tracking, hallucination rate monitoring (focuses on operational metrics, not RAG optimization)
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
Hands-on support from Deviniti—from kickoff through post-launch—direct access to the dev team.
Docs, training, and integrations are built around your stack, not one-size-fits-all.
Our services
24/7 customer support: Live chat and email support consistently praised in reviews (4.5/5 G2, 4.6/5 Capterra)
Developer documentation: Comprehensive at developers.livechat.com with Postman collections, video tutorials, code examples
Discord community: Developer community for technical discussions and peer support
Enterprise SLA: Available on custom contracts with guaranteed response times
User satisfaction: G2 rating 4.5/5 (761 reviews) with 68% five-star ratings, Capterra 4.6/5 (1,700+ reviews)
Common praise: "Responsive 24/7 support", "Ease of implementation", "Reliable platform"
Common criticisms: Rising prices, per-agent cost at scale, separate ChatBot purchase requirement, reduced mobile app functionality vs web
Documentation strength: Genuinely strong for chat APIs but lacks RAG-specific guidance (not applicable to platform architecture)
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.
Additional Considerations
Can build hybrid agents that run complex, transactional tasks—not just Q&A.
You own the solution end-to-end and can evolve it as AI tech moves forward.
Custom governance
Platform Classification: HUMAN-AGENT LIVE CHAT PLATFORM with AI augmentation, NOT a RAG-as-a-Service or autonomous chatbot platform - designed for agent productivity enhancement
Target Audience Clarity: Customer support teams needing live chat with AI suggestions vs developers requiring programmatic RAG control or autonomous knowledge retrieval
Primary Strength: Exceptional for human-agent customer support workflows with 200+ marketplace integrations and comprehensive compliance (SOC 2, GDPR, HIPAA, ISO 27001, PCI DSS, FedRAMP, CSA Star Level 1)
Compliance Leadership: Seven certifications including FedRAMP (federal government authorization rarely seen in chatbot platforms) and PCI DSS with built-in credit card masking for financial services readiness
Fragmented Product Ecosystem: ChatBot automation requires separate $52/month purchase ($52 × 12 = $624/year additional cost) rather than integrated no-code builder - users criticize fragmented product approach vs all-in-one competitors
Critical Limitation - Per-Agent Pricing Escalation: 10-agent Business team with ChatBot = $642/month ($59×10 + $52) = $7,704/year vs per-project pricing in RAG platforms - significant cost scaling concern noted in reviews
Knowledge Source Gap: Limited to PDFs and websites (max 2,000 pages, 10-30 files per plan) with NO support for DOCX, TXT, CSV, Excel, audio, video, code files - dramatically constrained vs 1,400+ formats in RAG platforms
NO Cloud Storage Integrations: No native sync with Google Drive, Dropbox, OneDrive, Notion, Confluence for knowledge sources - manual uploads only blocks automation workflows
Developer API Limitations: APIs serve chat operations (agent workflows, conversations, tickets) vs RAG operations (semantic search, retrieval, embeddings, knowledge base management) - fundamentally different focus
NO RAG Infrastructure: No vector database, embedding controls, chunking parameters, similarity thresholds, hybrid search, or anti-hallucination mechanisms with citation attribution - not designed for autonomous retrieval
Enterprise-Only SSO/SAML: Identity management features require highest tier creating significant barrier for mid-market companies with Okta, OneLogin, Auth0, or custom SAML requirements
Use Case Mismatch Warning: Comparing LiveChat to CustomGPT is architecturally misleading - different categories (human-agent live chat vs RAG-as-a-Service) serving different personas and value propositions
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.
No- Code Interface & Usability
No out-of-the-box no-code dashboard—IT or bespoke admin panels handle config.
Everyday users chat with the bot; deeper tweaks live with the tech team.
Visual builder: Visual drag-and-drop chatbot builder through separate ChatBot.com product ($52/month additional); core LiveChat focuses on agent dashboard and widget configuration rather than graphical flow design
Setup complexity: Consistently praised in reviews for "ease of implementation" and quick deployment; JavaScript snippet installation for website embedding with straightforward configuration wizard
Learning curve: G2 (4.5/5, 761 reviews) and Capterra (4.6/5, 1,700+ reviews) highlight user-friendly interface; agent dashboard designed for non-technical support teams with minimal training requirements
Pre-built templates: Widget theme presets for visual styles; ChatBot.com product offers automation templates but requires separate $52/month purchase (fragmented product ecosystem)
No-code workflows: 200+ marketplace integrations (Zapier, HubSpot, Salesforce, Zendesk) with no-code installation; e-commerce plugins (Shopify, WooCommerce, BigCommerce) with official native support
User experience: "Responsive 24/7 support", "reliable platform", "ease of implementation" consistently praised; criticisms focus on rising prices, per-agent cost at scale, and separate ChatBot purchase requirement rather than usability issues
LIMITATION: Chatbot automation requires separate ChatBot.com product purchase ($52/month) rather than integrated no-code builder; users criticize fragmented product ecosystem vs all-in-one platforms
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.
Competitive Positioning
Market position: Custom AI development agency (200+ clients served) specializing in self-hosted, enterprise RAG solutions with domain-specific fine-tuning and legacy system integration
Target customers: Large enterprises needing fully custom AI solutions, organizations with legacy systems requiring specialized integration, and companies requiring on-premises deployment with complete data sovereignty and compliance control
Key competitors: Azumo, internal AI development teams, Contextual.ai (enterprise), and other custom AI consulting firms
Competitive advantages: 200+ enterprise clients demonstrating proven track record, model-agnostic approach with fine-tuning on proprietary data, on-prem/private cloud deployment for full data control, custom API/workflow development tailored to exact specifications, white-glove support with direct dev team access, and complete solution ownership with bespoke UI/branding
Pricing advantage: Project-based pricing plus optional maintenance; higher upfront cost than SaaS but provides long-term ownership without subscription fees; best value for unique enterprise needs that can't be met with off-the-shelf solutions and require custom integrations
Use case fit: Ideal for enterprises with legacy systems needing specialized AI integration, organizations requiring domain-tuned models with insider terminology, companies needing hybrid AI agents handling complex transactional tasks beyond Q&A, and businesses demanding on-premises deployment with complete data sovereignty and custom compliance measures
vs CustomGPT: LiveChat excels in human-agent workflows with 200+ integrations and comprehensive compliance; CustomGPT excels in autonomous RAG retrieval with vector database controls and LLM selection
vs Intercom/Zendesk: LiveChat competes in live chat space with comparable features, pricing, and integration ecosystems - direct competitors
vs Drift: Both focus on conversational marketing and sales - LiveChat emphasizes support, Drift emphasizes revenue teams
vs RAG platforms (Vectara, Pinecone Assistant, Ragie): Fundamentally different architecture - LiveChat not designed for autonomous retrieval, lacks RAG infrastructure entirely
Market niche: Mature live chat platform for customer support teams with enterprise compliance requirements, NOT a RAG alternative for knowledge retrieval use cases
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
Model-agnostic approach: Supports any LLM - GPT-4, Claude, Llama 2, Falcon, Cohere, or custom models based on client needs
Custom model fine-tuning: Fine-tune models on proprietary data for domain-specific terminology and insider jargon
Local LLM deployment: On-premises model hosting for complete data sovereignty and offline operation
Multiple model support: Deploy different models for different use cases within same infrastructure
Model flexibility: Swap models through new build/deploy cycle as requirements evolve
Custom training pipelines: Build specialized training workflows for continuous model improvement
Proprietary AI Engine: ChatBot.com uses internal NLP system, explicitly doesn't rely on Google Bard, OpenAI, or Bing AI
NO LLM Model Selection: Cannot choose between GPT-3.5, GPT-4, Claude, Gemini, or custom models - proprietary engine only
Opaque Architecture: Model architecture, training data, and capabilities not publicly documented
AI Reply Suggestions: Knowledge base-powered response recommendations for human agents based on conversation context
Text Enhancement AI: Grammar correction and tone polishing for agent messages before sending
AI Insights: Analyzes 1,000+ customer queries in 30 seconds to identify trends and patterns
CRITICAL LIMITATION: No flexibility for model routing, fine-tuning, or BYOLLM capabilities - rated 3/10 for model flexibility vs RAG platforms
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
Custom RAG architecture: Best-practice retrieval with multi-index strategies and tuned prompts for precise answers
Domain-specific fine-tuning: Train on proprietary data to eliminate hallucinations and improve accuracy for insider terminology
Custom channel deployment: Integrate into any channel - web, mobile, Slack, Teams, or legacy applications
Domain-tuned assistants: Specialized agents with fine-tuned models for technical or medical terminology
Customer Support Teams: Live chat for customer service with human agents augmented by AI suggestions - primary use case for 37,000+ businesses
E-commerce: Real-time customer assistance during shopping with Shopify, WooCommerce, BigCommerce native integrations
Sales Engagement: Lead qualification and conversion through live agent interactions with CRM integrations (Salesforce, HubSpot)
Multi-Channel Support: Omnichannel customer engagement across website, Facebook Messenger, WhatsApp Business, Apple Messages, Telegram, SMS
Agent Productivity: AI-powered reply suggestions, text enhancement, tag suggestions, and summaries to improve agent efficiency
Enterprise Helpdesk: Integration with Zendesk, Intercom, HelpDesk ticketing for comprehensive support workflows
NOT SUITABLE FOR: Autonomous knowledge retrieval requiring RAG accuracy controls, developer-focused programmatic document search, or applications needing LLM flexibility
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)
Per-Agent Pricing Model: Cost escalates at scale - 10-agent Business team with ChatBot = $642/month ($59×10 + $52)
CONCERN: Criticized in reviews for "rising prices" and "cost structure at scale" issue vs token/project-based pricing in RAG competitors
Hidden Costs: HIPAA compliance requires Enterprise plan with $100/seat minimum and 5-seat commitment ($6,000/year minimum)
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
White-glove support: Direct access to development team from kickoff through post-launch
Custom documentation: Tailored documentation for your specific implementation and tech stack
Training programs: Custom training for IT teams and end users on solution usage and maintenance
Dedicated project manager: Single point of contact throughout development lifecycle
Post-launch support: Optional maintenance contracts with SLA guarantees and priority response
Integration support: Hands-on help connecting to existing enterprise systems and workflows
Knowledge transfer: Complete handoff of code, architecture docs, and operational runbooks
Enterprise focus: Proven experience with large-scale deployments and complex requirements
24/7 Customer Support: Live chat and email support consistently praised in reviews (4.5/5 G2, 4.6/5 Capterra) - "Responsive 24/7 support"
User Satisfaction: G2 rating 4.5/5 (761 reviews, 68% five-star), Capterra 4.6/5 (1,700+ reviews) - "Ease of implementation" and "Reliable platform" common themes
Developer Documentation: Comprehensive at developers.livechat.com with Postman collections, video tutorials, code examples
Discord Community: Developer community for technical discussions and peer support
Enterprise SLA: Available on custom contracts with guaranteed response times and uptime commitments
API Documentation: REST API and WebSocket (RTM) documentation with OAuth 2.1 PKCE guides and rate limit details (180 req/min per API key)
SDK Support: JavaScript/Node.js (@livechat/chat-sdk), iOS (Swift SDK), Android (Kotlin), Customer SDK for widget development
Documentation Strength: Genuinely strong for chat APIs and agent workflows, but lacks RAG-specific guidance (not applicable to platform architecture)
Common Criticisms: Rising prices, per-agent cost at scale, separate ChatBot purchase requirement, reduced mobile app functionality vs web
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
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
High upfront cost: $50K-$500K+ initial development vs $29-$999/month SaaS solutions
Longer time to value: 2-6 month development cycle vs instant SaaS deployment
Custom maintenance required: Updates and changes require development work, not self-service
No out-of-box features: Everything built from scratch - no pre-built templates or no-code tools
Technical expertise required: IT team needed for ongoing management and infrastructure
Project-based approach: Each enhancement or change may require additional development sprint
Not for budget-constrained SMBs: Best suited for large enterprises with significant AI budgets
Best for unique needs only: Only justified when off-the-shelf solutions cannot meet requirements
NOT a RAG Platform: Fundamental architecture designed for human-agent live chat, not autonomous knowledge retrieval (rated 2/10 as RAG platform)
Limited File Formats: PDFs and website crawling only (max 2,000 pages) - NO support for DOCX, TXT, CSV, Excel, audio, video, code files (vs 1,400+ formats in RAG platforms)
NO Cloud Storage Integrations: No native sync with Google Drive, Dropbox, OneDrive, Notion, Confluence - manual uploads only
NO LLM Flexibility: Proprietary AI engine only - cannot choose GPT-4, Claude, Gemini, or custom models
NO RAG Infrastructure: No vector database, embedding controls, chunking parameters, similarity thresholds, hybrid search, or anti-hallucination mechanisms
Fragmented Product Ecosystem: ChatBot automation requires separate $52/month purchase vs integrated no-code builders in competitors
Per-Agent Pricing Escalation: Cost structure criticized in reviews - scales expensively vs per-project pricing (10 agents + ChatBot = $642/month)
Enterprise-Only Features: White-labeling, SSO/SAML, HIPAA BAA require Enterprise plan with minimum 5 seats at $100/seat ($6,000/year minimum)
NO API for RAG Operations: APIs serve chat operations (agent workflows, conversations, tickets) vs RAG operations (semantic search, retrieval, embeddings)
Limited to 180 req/min: API rate limits may constrain high-volume applications
NO Python SDK: JavaScript/Node.js/mobile only - limits backend integration for Python-based systems
Competitive Positioning: Different category from CustomGPT - excellent for human-agent customer support, inappropriate for autonomous retrieval requiring accuracy controls
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
Custom AI Agents: Build autonomous agents using advanced LLM architecture with planning modules, memory systems, and RAG pipelines tailored to exact business requirements
Agent Development
Planning Module: Agents break down complex tasks into smaller manageable steps using task decomposition methods - enabling multi-step autonomous workflows
Memory System: Retains past interactions ensuring consistent responses in long-running workflows, maintaining context to improve handling of complex tasks over time
RAG Integration: Agents use specialized RAG pipelines, code interpreters, and external APIs to gather and process data efficiently - enhancing ability to access and use external resources for accurate outcomes
RAG Implementation
Tool & API Integration: Agents execute actions beyond Q&A - integrate with CRMs, ERPs, ITSM tools, proprietary APIs, and legacy systems through custom webhooks and endpoints
Domain-Tuned Behavior: Fine-tune on proprietary data for insider terminology, multi-turn memory with context preservation, and any language support including local LLM deployment
Hybrid Agent Capabilities: Build agents that run complex transactional tasks beyond simple Q&A - handle workflows like IT ticket creation, CRM updates, and approval processes
Hybrid Agents
Real-World Proven: Deployed AI Agent in Credit Agricole bank for customer service automation - routes simple queries automatically, flags complex ones for human support, and drafts personalized replies
Text Copilot: AI assistant helping agents navigate the LiveChat platform efficiently
AI Reply Suggestions: Recommends responses from knowledge sources based on conversation context
Text Enhancement: Grammar correction and tone polishing for agent messages before sending
Tag Suggestions: Automatic conversation categorization and tagging for organization
AI Summaries: Conversation summarization for agent handoffs and context transfer
AI Insights: Analyzes 1,000+ customer queries in 30 seconds to identify trends and patterns
Human-agent focus: AI features designed to augment agent productivity, not replace human interaction
CRITICAL LIMITATION: No NO anti-hallucination controls - responses cannot be traced to source documents with citations (vs RAG platforms with citation attribution)
CRITICAL LIMITATION: No NO retrieval parameter configuration - users cannot adjust similarity thresholds, implement hybrid search strategies, or configure confidence scoring
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 A G-as-a- Service Assessment
Platform Type: CUSTOM AI DEVELOPMENT CONSULTANCY - not a platform but professional services firm building bespoke enterprise RAG solutions and AI agents from scratch (200+ clients served)
Core Offering: Project-based custom development of self-hosted AI agents, RAG architectures, and LLM applications tailored to exact specifications - not pre-built software or SaaS
Agent Capabilities: Build fully autonomous AI agents with planning modules, memory systems, RAG pipelines, and tool integration - proven in regulated industries like banking (Credit Agricole deployment)
Agent Services
Developer Experience: White-glove professional services with dedicated dev team, project-specific API development (JSON over HTTP), custom documentation and samples, hands-on support from kickoff through post-launch
No-Code Capabilities: NONE - everything requires custom development work. No dashboard, visual builders, or self-service tools. IT teams or bespoke admin panels handle configuration post-delivery
Target Market: Large enterprises with legacy systems needing specialized AI integration, organizations requiring on-premises deployment with complete data sovereignty, companies with unique needs that can't be met with off-the-shelf solutions
RAG Technology Approach: Best-practice retrieval with multi-index strategies, tuned prompts, fine-tuning on proprietary data to eliminate hallucinations, custom vector DB selection, and hybrid search strategies tailored to data characteristics
RAG Approach
Deployment Model: On-prem or private cloud only - complete data control with no cloud vendor dependencies, custom infrastructure managed by client, strong encryption and access controls integrated with existing security stack
Enterprise Readiness: ISO 27001 certification, GDPR and CCPA compliance, custom compliance measures for HIPAA or industry-specific requirements, AES-256 encryption, RBAC integrated with existing identity management
Pricing Model: Project-based $50K-$500K+ initial development plus optional ongoing maintenance contracts - higher upfront cost but no recurring SaaS fees, full solution ownership
Use Case Fit: Enterprises with legacy systems needing specialized AI integration, domain-tuned models with insider terminology, hybrid AI agents handling complex transactional tasks, on-premises deployment with complete data sovereignty
NOT A PLATFORM: Does not offer self-service software, API-as-a-service, or turnkey solutions - exclusively custom development consultancy requiring sales engagement and multi-month build cycles
Competitive Positioning: Competes with other AI consultancies (Azumo, internal AI teams) and enterprise RAG platforms - differentiates through 200+ client track record, regulated industry expertise (banking, legal), and complete customization
Platform classification: HUMAN-AGENT LIVE CHAT PLATFORM with AI augmentation, NOT a RAG-as-a-Service platform
Architecture philosophy: Designed for agent productivity enhancement, not autonomous knowledge retrieval
Target audience: Customer support teams needing live chat with AI suggestions vs developers requiring programmatic RAG control
Missing RAG foundations: NO vector database, NO embedding controls, NO LLM model selection, NO anti-hallucination mechanisms, NO retrieval configuration APIs
Knowledge source gap: Limited to PDFs and websites (max 2,000 pages, 10-30 files) vs 1,400+ formats in RAG platforms
API focus: Chat operations (agent workflows, conversations, tickets) vs RAG operations (semantic search, retrieval, embeddings)
Use case fit: Excellent for human-agent customer support, inappropriate for autonomous retrieval requiring accuracy controls
Competitive positioning: Different category from CustomGPT - live chat vs RAG-as-a-Service (rated 2/10 as RAG platform - fundamentally different architecture)
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
200+ Integration Ecosystem ( Core Differentiator)
N/A
Mature marketplace advantage: 200+ pre-built integrations after 20+ years of development vs newer platforms' narrower ecosystems
Enterprise CRM/helpdesk depth: Deep integrations with Salesforce, HubSpot, Zendesk, Intercom for seamless customer data flow
E-commerce official support: Native Shopify/WooCommerce/BigCommerce plugins demonstrate platform validation
Webhook flexibility: JSON payload support with 10-second timeouts allows custom integrations for unique business requirements (8/10 rated differentiator)
Visual drag-and-drop builder: No-code chatbot creation with NLP intent recognition
Proprietary AI engine: ChatBot.com explicitly states it "doesn't rely on third-party providers like Google Bard, OpenAI, or Bing AI" - everything runs on internal NLP system
Pricing: $52/month additional cost on top of LiveChat subscription (fragmented product ecosystem)
Traditional chatbot architecture: Resembles rule-based chatbot platforms rather than RAG systems with semantic retrieval
Integration requirement: Purchased and integrated separately from LiveChat core product
LIMITATION: No NO LLM model selection or routing - proprietary engine only, eliminating GPT-4, Claude, Gemini, or custom model options entirely (6/10 rated as limitation vs true RAG platforms)
N/A
Widget Customization & White- Labeling
N/A
Live editor: Visual customization with theme presets, color pickers (custom hex supported), logo uploads, position controls
Light/dark modes: Built-in theme switching with user preference detection
Custom CSS: Advanced styling capabilities for design control beyond presets
WCAG 2.1 AA compliance: Accessibility support with screen readers and keyboard navigation
Mobile responsiveness: Separate mobile widget settings with device-specific hiding options
Domain restrictions: Control which websites can embed the widget through trusted domains configuration
White-labeling (Enterprise only): Note: Complete branding removal requires Enterprise plan (custom pricing, minimum 5 seats) - not available on lower tiers
Role-based access: Owner, Admin, and Agent roles with configurable permissions, agent groups for departmental routing
N/A
R A G Implementation & Accuracy
N/A
CRITICAL ARCHITECTURAL GAP: No NOT a RAG-as-a-Service platform - no vector database, embedding controls, or configurable retrieval pipeline
NO chunking parameters: No Chunk size, overlap, and strategy not exposed for optimization
NO embedding model selection: No Cannot choose between OpenAI, Cohere, or custom embedding models
NO similarity threshold controls: No Cannot configure cosine similarity thresholds or retrieval scoring
NO hybrid search: No No combination of keyword and semantic search strategies
NO anti-hallucination mechanisms: No No citation attribution, source verification, or confidence scoring - responses cannot be traced to source documents
Proprietary processing: Knowledge base processing happens through opaque internal system without transparency into retrieval methodology
Competitive positioning: LiveChat serves chat operations, not autonomous knowledge retrieval - fundamentally different architecture from RAG platforms (rated 2/10 as RAG platform - not designed for this use case)
After analyzing features, pricing, performance, and user feedback, both Deviniti and LiveChat are capable platforms that serve different market segments and use cases effectively.
When to Choose Deviniti
You value strong compliance and security focus
Self-hosted solutions for data privacy
Domain expertise in regulated industries
Best For: Strong compliance and security focus
When to Choose LiveChat
You value mature 20+ year platform with proven enterprise reliability (adobe, paypal, ikea, samsung, best buy)
200+ integrations with robust Zapier support (5,000+ app connections) and comprehensive webhooks
Best For: Mature 20+ year platform with proven enterprise reliability (Adobe, PayPal, IKEA, Samsung, Best Buy)
Migration & Switching Considerations
Switching between Deviniti and LiveChat 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
Deviniti starts at custom pricing, while LiveChat begins at $20/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 Deviniti and LiveChat 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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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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