LiveChat vs SciPhi

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

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Priyansh Khodiyar's avatar
Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare LiveChat and SciPhi across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.

Overview

When choosing between LiveChat and SciPhi, understanding their unique strengths and architectural differences is crucial for making an informed decision. Both platforms serve the RAG (Retrieval-Augmented Generation) space but cater to different use cases and organizational needs.

Quick Decision Guide

  • Choose LiveChat if: you value mature 20+ year platform with proven enterprise reliability (adobe, paypal, ikea, samsung, best buy)
  • Choose SciPhi if: you value state-of-the-art retrieval accuracy

About LiveChat

LiveChat Landing Page Screenshot

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

About SciPhi

SciPhi Landing Page Screenshot

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

Overall Rating
89/100
Starting Price
Custom

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: Customer Support versus RAG Platform. These differences make each platform better suited for specific use cases and organizational requirements.

⚠️ What This Comparison Covers

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

Detailed Feature Comparison

logo of livechat
LiveChat
logo of sciphi
SciPhi
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CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
  • Supported formats – PDFs and website crawling only (max 2,000 pages)
  • Plan limits – Team: 10 files/3 sites, Business: 30 files/10 sites
  • ⚠️ NO DOCX, TXT, CSV, Excel – No audio, video, code files (vs 1,400+ formats)
  • ⚠️ NO cloud storage sync – No Google Drive, Dropbox, OneDrive, Notion, Confluence
  • Handles 40 + formats—from PDFs and spreadsheets to audio—at massive scale Reference.
  • Async ingest auto-scales, crunching millions of tokens per second—perfect for giant corpora Benchmark details.
  • Ingest via code or API, so you can tap proprietary databases or custom pipelines with ease.
  • 1,400+ file formats – PDF, DOCX, Excel, PowerPoint, Markdown, HTML + auto-extraction from ZIP/RAR/7Z archives
  • Website crawling – Sitemap indexing with configurable depth for help docs, FAQs, and public content
  • Multimedia transcription – AI Vision, OCR, YouTube/Vimeo/podcast speech-to-text built-in
  • Cloud integrations – Google Drive, SharePoint, OneDrive, Dropbox, Notion with auto-sync
  • Knowledge platforms – Zendesk, Freshdesk, HubSpot, Confluence, Shopify connectors
  • Massive scale – 60M words (Standard) / 300M words (Premium) per bot with no performance degradation
Integrations & Channels
  • Messaging platforms – Website, Facebook, WhatsApp, Apple Messages, Telegram, SMS, email
  • 200+ marketplace integrations – Zapier (5,000+ apps), HubSpot, Salesforce, Zendesk, Intercom
  • E-commerce platforms – Shopify, WooCommerce, BigCommerce native plugins
  • ✅ Custom integrations – Webhooks with JSON payloads, 10s response timeout
  • Ships a REST RAG API—plug it into websites, mobile apps, internal tools, or even legacy systems.
  • No off-the-shelf chat widget; you wire up your own front end API snippet.
  • Website embedding – Lightweight JS widget or iframe with customizable positioning
  • CMS plugins – WordPress, WIX, Webflow, Framer, SquareSpace native support
  • 5,000+ app ecosystem – Zapier connects CRMs, marketing, e-commerce tools
  • MCP Server – Integrate with Claude Desktop, Cursor, ChatGPT, Windsurf
  • OpenAI SDK compatible – Drop-in replacement for OpenAI API endpoints
  • LiveChat + Slack – Native chat widgets with human handoff capabilities
200+ Integration Ecosystem ( Core Differentiator)
  • ✅ Mature marketplace – 200+ pre-built integrations after 20+ years development
  • ✅ Enterprise CRM depth – Deep Salesforce, HubSpot, Zendesk, Intercom integrations
  • ✅ E-commerce validated – Official Shopify/WooCommerce/BigCommerce plugins
  • ✅ Webhook flexibility – JSON payloads, 10s timeouts for custom workflows (8/10 differentiator)
N/A
N/A
Agent Chat A P I v3.5 ( Differentiator)
  • Dual transport – REST API and WebSocket (RTM) for real-time communication
  • Official SDKs – JavaScript/Node.js, iOS (Swift), Android (Kotlin), Customer SDK
  • OAuth 2.1 PKCE – Modern auth plus Personal Access Tokens
  • ⚠️ Rate limits – 180 requests/min may constrain high-volume apps
  • ⚠️ Chat ops focus – No RAG APIs for semantic search or embedding management
N/A
N/A
Core Agent Features
  • AI Reply Suggestions – Context-based response recommendations from knowledge sources
  • Text Enhancement – Grammar correction and tone polishing before sending
  • AI Insights – Analyzes 1,000+ queries in 30s for trends
  • ⚠️ NO anti-hallucination – No citation attribution or source tracing
  • Agentic RAG – Reasoning agent for autonomous research across documents/web with multi-step problem solving
  • Advanced Toolset – Semantic search, metadata search, document retrieval, web search, web scraping capabilities
  • Multi-Turn Context – Stateful dialogues maintaining conversation history via conversation_id for follow-ups
  • Citation Transparency – Detailed responses with source citations for fact-checking and verification
  • ⚠️ No Pre-Built UI – API-first platform requires custom front-end development
  • ⚠️ No Lead Analytics – Lead capture and dashboards must be implemented at application layer
  • Custom AI Agents – Autonomous GPT-4/Claude agents for business tasks
  • Multi-Agent Systems – Specialized agents for support, sales, knowledge
  • Memory & Context – Persistent conversation history across sessions
  • Tool Integration – Webhooks + 5,000 Zapier apps for automation
  • Continuous Learning – Auto re-indexing without manual retraining
Chat Bot Automation ( Separate Product)
  • Visual builder – Drag-and-drop no-code chatbot with NLP
  • Proprietary engine – Internal NLP, doesn't use OpenAI/Bard/Bing
  • ⚠️ Additional cost – $52/month on top of LiveChat subscription
  • ⚠️ NO LLM selection – Proprietary only, no GPT-4/Claude/Gemini access
N/A
N/A
Widget Customization & White- Labeling
  • Live editor – Theme presets, custom hex colors, logo uploads, positioning
  • WCAG 2.1 AA – Accessibility with screen readers, keyboard navigation
  • Mobile responsive – Device-specific settings and hiding options
  • ⚠️ White-label Enterprise only – Requires custom pricing, minimum 5 seats
N/A
N/A
L L M Model Options
  • ⚠️ NO model selection – Proprietary AI engine only
  • ⚠️ NO GPT-4, Claude, Gemini – Cannot choose LLM providers
  • ⚠️ NO BYOLLM – No custom models or fine-tuning
  • ⚠️ Opaque processing – Architecture and training data not documented (3/10 flexibility)
  • LLM-agnostic—GPT-4, Claude, Llama 2, you choose.
  • Pick, fine-tune, or swap models anytime to balance cost and performance Model options.
  • GPT-5.1 models – Latest thinking models (Optimal & Smart variants)
  • GPT-4 series – GPT-4, GPT-4 Turbo, GPT-4o available
  • Claude 4.5 – Anthropic's Opus available for Enterprise
  • Auto model routing – Balances cost/performance automatically
  • Zero API key management – All models managed behind the scenes
Developer Experience ( A P I & S D Ks)
  • Agent Chat API v3.5 – REST and WebSocket with OAuth 2.1 PKCE
  • Mobile SDKs – iOS (Swift, iOS 15.6+), Android (Kotlin via Gradle)
  • ✅ Strong documentation – Postman collections, tutorials, Discord community
  • ⚠️ NO Python SDK – JavaScript/mobile only, limits backend integration
  • REST API plus a Python client (R2RClient) handle ingest and query tasks
  • Docs and GitHub repos offer deep dives and open-source starter code SciPhi GitHub.
  • REST API – Full-featured for agents, projects, data ingestion, chat queries
  • Python SDK – Open-source customgpt-client with full API coverage
  • Postman collections – Pre-built requests for rapid prototyping
  • Webhooks – Real-time event notifications for conversations and leads
  • OpenAI compatible – Use existing OpenAI SDK code with minimal changes
R A G Implementation & Accuracy
  • ⚠️ NOT RAG-as-a-Service – No vector database, embeddings, retrieval pipeline
  • ⚠️ NO chunking/embedding controls – Size, overlap, model selection not exposed
  • ⚠️ NO hybrid search – No keyword + semantic combination
  • ⚠️ NO anti-hallucination – No citations, source verification (2/10 RAG platform)
N/A
N/A
Performance & Accuracy
  • Real-time delivery – Sub-second message delivery, praised for reliability
  • Scalability – 37,000+ businesses, enterprise customers (Adobe, PayPal, IKEA)
  • ⚠️ NO accuracy benchmarks – No published AI retrieval metrics
  • ⚠️ Operational focus – Metrics for queue times, agent response, not AI accuracy
  • Hybrid search (dense + keyword) keeps retrieval fast and sharp.
  • Knowledge-graph boosts (HybridRAG) drive up to 150 % better accuracy
  • Sub-second latency—even at enterprise scale.
  • Sub-second responses – Optimized RAG with vector search and multi-layer caching
  • Benchmark-proven – 13% higher accuracy, 34% faster than OpenAI Assistants API
  • Anti-hallucination tech – Responses grounded only in your provided content
  • OpenGraph citations – Rich visual cards with titles, descriptions, images
  • 99.9% uptime – Auto-scaling infrastructure handles traffic spikes
Security & Privacy
  • ✅ Seven certifications – SOC 2, GDPR, HIPAA, ISO 27001, PCI DSS, FedRAMP, CSA Star
  • Encryption – TLS transit, AES-256 at rest
  • Data residency – EU (Poland) compliance with account isolation
  • ⚠️ SSO/SAML Enterprise only – Significant gap for mid-market identity management
  • Customer data stays isolated in SciPhi Cloud; self-host for full control.
  • Standard encryption in transit and at rest; tune self-hosted setups to meet any regulation.
  • SOC 2 Type II + GDPR – Third-party audited compliance
  • Encryption – 256-bit AES at rest, SSL/TLS in transit
  • Access controls – RBAC, 2FA, SSO, domain allowlisting
  • Data isolation – Never trains on your data
Full Compliance Portfolio ( Core Differentiator)
  • ✅ Seven certifications – SOC 2, GDPR, HIPAA, ISO 27001, PCI DSS, FedRAMP, CSA Star
  • ✅ FedRAMP unique – Rare federal authorization enables government contracts
  • ✅ PCI DSS masking – Built-in payment card protection for financial services
  • ✅ HIPAA BAA – Business Associate Agreement for healthcare compliance (9/10 differentiator)
N/A
N/A
Observability & Monitoring
  • Real-time monitoring – Agent status, queue depth, visitor activity dashboards
  • Chat metrics – Volume, missed chats, response times, agent performance, CSAT
  • Staffing predictions – AI scheduling optimization (Business+ plans)
  • ⚠️ NO AI metrics – No retrieval accuracy, semantic search, hallucination monitoring
  • Dev dashboard shows real-time logs, latency, and retrieval quality Dashboard.
  • Hook into Prometheus, Grafana, or other tools for deep monitoring.
  • Real-time dashboard – Query volumes, token usage, response times
  • Customer Intelligence – User behavior patterns, popular queries, knowledge gaps
  • Conversation analytics – Full transcripts, resolution rates, common questions
  • Export capabilities – API export to BI tools and data warehouses
Pricing & Scalability
  • Starter – $20/agent/month, 60-day history, 1 user
  • Team – $41/agent/month, unlimited history, 10 files/3 sites
  • Business – $59/agent/month, staffing predictions, 30 files/10 sites
  • Enterprise – Custom pricing, min 5 seats, SSO/SAML, white-label, HIPAA
  • ⚠️ Cost escalation – 10 agents + ChatBot = $642/month ($7,704/year)
  • Free tier plus a $25/mo Dev tier for experiments.
  • Enterprise plans with custom pricing and self-hosting for heavy traffic Pricing.
  • Standard: $99/mo – 60M words, 10 bots
  • Premium: $449/mo – 300M words, 100 bots
  • Auto-scaling – Managed cloud scales with demand
  • Flat rates – No per-query charges
Support & Ecosystem
  • ✅ 24/7 support – Live chat and email, consistently praised (4.5/5 G2, 4.6/5 Capterra)
  • Developer docs – Extensive at developers.livechat.com with Postman, tutorials
  • Enterprise SLA – Guaranteed response times on custom contracts
  • Common criticisms – Rising prices, per-agent scaling costs, fragmented ChatBot product
  • Community help via Discord and GitHub; Enterprise customers get dedicated support
  • Open-source core encourages community contributions and integrations.
  • Comprehensive docs – Tutorials, cookbooks, API references
  • Email + in-app support – Under 24hr response time
  • Premium support – Dedicated account managers for Premium/Enterprise
  • Open-source SDK – Python SDK, Postman, GitHub examples
  • 5,000+ Zapier apps – CRMs, e-commerce, marketing integrations
Additional Considerations
  • ⚠️ Platform classification – Human-agent live chat with AI, NOT RAG-as-a-Service
  • ✅ Primary strength – Customer support workflows with 200+ integrations, seven certifications
  • ⚠️ Knowledge gap – PDFs/websites only, NO DOCX/CSV/Excel/audio/video/code files
  • ⚠️ NO RAG infrastructure – No vector DB, embeddings, chunking, similarity thresholds
  • Advanced extras like GraphRAG and agentic flows push beyond basic Q&A
  • Great fit for enterprises needing deeply customized, fully integrated AI solutions.
  • Time-to-value – 2-minute deployment vs weeks with DIY
  • Always current – Auto-updates to latest GPT models
  • Proven scale – 6,000+ organizations, millions of queries
  • Multi-LLM – OpenAI + Claude reduces vendor lock-in
A I Models
  • Proprietary engine – Internal NLP, doesn't rely on OpenAI/Bard/Bing
  • ⚠️ NO LLM selection – Cannot choose GPT-4, Claude, Gemini
  • ⚠️ Opaque architecture – Model training data, capabilities not documented
  • ⚠️ NO BYOLLM – No model routing, fine-tuning, custom models (3/10 flexibility)
  • LLM-Agnostic Architecture – GPT-4, GPT-3.5, Claude, Llama 2, and other open-source models
  • Model Flexibility – Easy swapping to balance cost/performance without vendor lock-in
  • Custom Support – Configure any LLM via API including fine-tuned or proprietary models
  • Embedding Providers – Multiple embedding options for semantic search and vector generation
  • ✅ Full control over temperature, max tokens, and generation parameters
  • OpenAI – GPT-5.1 (Optimal/Smart), GPT-4 series
  • Anthropic – Claude 4.5 Opus/Sonnet (Enterprise)
  • Auto-routing – Intelligent model selection for cost/performance
  • Managed – No API keys or fine-tuning required
R A G Capabilities
  • ⚠️ NOT RAG platform – No vector DB, embedding controls, retrieval pipeline
  • ⚠️ Limited sources – PDFs and websites only (max 2,000 pages, 10-30 files)
  • ⚠️ Human-agent focus – Agent workflows, not autonomous retrieval (2/10 RAG rating)
  • HybridRAG Technology – Vector search + knowledge graphs for 150% accuracy improvement
  • Hybrid Search – Dense vector + keyword with reciprocal rank fusion
  • Agentic RAG – Reasoning agent for autonomous research across documents and web
  • Multimodal Ingestion – 40+ formats (PDFs, spreadsheets, audio) at massive scale
  • ✅ Millions of tokens/second async auto-scaling ingestion throughput
  • ✅ Sub-second latency even at enterprise scale with optimized operations
  • GPT-4 + RAG – Outperforms OpenAI in independent benchmarks
  • Anti-hallucination – Responses grounded in your content only
  • Automatic citations – Clickable source links in every response
  • Sub-second latency – Optimized vector search and caching
  • Scale to 300M words – No performance degradation at scale
Use Cases
  • ✅ Customer support – Live chat for 37,000+ businesses with AI agent augmentation
  • ✅ E-commerce – Shopify/WooCommerce/BigCommerce native integrations
  • ✅ Multi-channel – Website, Facebook, WhatsApp, Apple Messages, Telegram, SMS
  • ⚠️ NOT suitable for – Autonomous knowledge retrieval, programmatic document search
  • Enterprise Knowledge – Process millions of documents with knowledge graph relationships
  • Support Automation – RAG-powered support bots with accurate, grounded responses
  • Research & Analysis – Agentic RAG for autonomous research across collections and web
  • Compliance & Legal – Large document repositories with precise citation tracking
  • Internal Docs – Developer-focused RAG for code, API references, technical knowledge
  • Custom AI Apps – API-first architecture integrates into any application or workflow
  • Customer support – 24/7 AI handling common queries with citations
  • Internal knowledge – HR policies, onboarding, technical docs
  • Sales enablement – Product info, lead qualification, education
  • Documentation – Help centers, FAQs with auto-crawling
  • E-commerce – Product recommendations, order assistance
Security & Compliance
  • ✅ Seven certifications – SOC 2, GDPR, HIPAA, ISO 27001, PCI DSS, FedRAMP, CSA Star
  • ✅ Data privacy – Customer data never used for training, zero-retention policies
  • Encryption – TLS transit, AES-256 at rest, regional data residency
  • ⚠️ HIPAA/SSO Enterprise only – Min 5 seats ($6,000/year minimum)
  • Data Isolation – Single-tenant architecture with isolated customer data in SciPhi Cloud
  • Self-Hosting Option – On-premise deployment for complete data control in regulated industries
  • Encryption Standards – TLS in transit, AES-256 at rest encryption
  • Access Controls – Document-level granular permissions with role-based access control (RBAC)
  • ✅ Open-source R2R core enables security audits and compliance validation
  • ✅ Self-hosted deployments tunable for HIPAA, SOC 2, and other regulations
  • SOC 2 Type II + GDPR – Regular third-party audits, full EU compliance
  • 256-bit AES encryption – Data at rest; SSL/TLS in transit
  • SSO + 2FA + RBAC – Enterprise access controls with role-based permissions
  • Data isolation – Never trains on customer data
  • Domain allowlisting – Restrict chatbot to approved domains
Pricing & Plans
  • Starter – $20/agent/month, 60-day history, 1 user
  • Team – $41/agent/month, unlimited history, 400 users, AI features
  • Business – $59/agent/month, staffing predictions, full AI features
  • Enterprise – Custom pricing (min 5 seats), SSO/SAML, white-label, HIPAA
  • ⚠️ Cost escalation – Per-agent model criticized for scaling vs project pricing
  • Free Tier – Generous no-credit-card tier for experimentation and development
  • Developer Plan – $25/month for individual developers and small projects
  • Enterprise Plans – Custom pricing based on scale, features, and support
  • Self-Hosting – Open-source R2R available free (infrastructure costs only)
  • ✅ Flat subscription pricing without per-query or per-document charges
  • ✅ Managed cloud handles infrastructure, deployment, scaling, updates, maintenance
  • Standard: $99/mo – 10 chatbots, 60M words, 5K items/bot
  • Premium: $449/mo – 100 chatbots, 300M words, 20K items/bot
  • Enterprise: Custom – SSO, dedicated support, custom SLAs
  • 7-day free trial – Full Standard access, no charges
  • Flat-rate pricing – No per-query charges, no hidden costs
Support & Documentation
  • ✅ 24/7 support – Live chat/email, consistently praised (4.5/5 G2, 4.6/5 Capterra)
  • Developer docs – Extensive at developers.livechat.com with Postman, tutorials
  • Enterprise SLA – Guaranteed response times, uptime commitments
  • SDK support – JavaScript, iOS (Swift), Android (Kotlin), Customer SDK
  • Comprehensive Docs – Detailed docs at r2r-docs.sciphi.ai covering all features and endpoints
  • GitHub Repository – Active open-source development at github.com/SciPhi-AI/R2R with code examples
  • Community Support – Discord community and GitHub issues for peer support
  • Enterprise Support – Dedicated channels for enterprise customers with SLAs
  • ✅ Python client (R2RClient) with extensive examples and starter code
  • ✅ Developer dashboard with real-time logs, latency, and retrieval quality metrics
  • Documentation hub – Docs, tutorials, API references
  • Support channels – Email, in-app chat, dedicated managers (Premium+)
  • Open-source – Python SDK, Postman, GitHub examples
  • Community – User community + 5,000 Zapier integrations
Limitations & Considerations
  • ⚠️ NOT RAG platform – Human-agent live chat, not autonomous retrieval (2/10 RAG)
  • ⚠️ Limited formats – PDFs/websites only, NO DOCX/CSV/Excel/audio/video/code
  • ⚠️ NO LLM flexibility – Proprietary engine only, no GPT-4/Claude/Gemini
  • ⚠️ Fragmented product – ChatBot requires separate $52/month purchase
  • ⚠️ Cost scaling – Per-agent pricing criticized, 10 agents = $642/month
  • ⚠️ Developer-Focused – Requires technical expertise to build and wire custom front ends
  • ⚠️ Infrastructure Requirements – Self-hosting needs GPU infrastructure and DevOps expertise
  • ⚠️ Integration Effort – API-first design means building your own chat UI
  • ⚠️ Learning Curve – Advanced features like knowledge graphs require RAG concept understanding
  • ⚠️ Community Support Limits – Open-source support relies on community unless enterprise plan
  • Managed service – Less control over RAG pipeline vs build-your-own
  • Model selection – OpenAI + Anthropic only; no Cohere, AI21, open-source
  • Real-time data – Requires re-indexing; not ideal for live inventory/prices
  • Enterprise features – Custom SSO only on Enterprise plan
Core Chatbot Features
N/A
  • Core RAG engine serves retrieval-grounded answers; hook it to your UI for multi-turn chat.
  • Multi-lingual if the LLM you pick supports it.
  • Lead-capture or human handoff flows are yours to build through the API.
  • ✅ #1 accuracy – Median 5/5 in independent benchmarks, 10% lower hallucination than OpenAI
  • ✅ Source citations – Every response includes clickable links to original documents
  • ✅ 93% resolution rate – Handles queries autonomously, reducing human workload
  • ✅ 92 languages – Native multilingual support without per-language config
  • ✅ Lead capture – Built-in email collection, custom forms, real-time notifications
  • ✅ Human handoff – Escalation with full conversation context preserved
Customization & Branding
N/A
  • Fully bespoke—design any UI you want and skin it to match your brand.
  • SciPhi focuses on the back end, so front-end look-and-feel is entirely up to you.
  • Full white-labeling included – Colors, logos, CSS, custom domains at no extra cost
  • 2-minute setup – No-code wizard with drag-and-drop interface
  • Persona customization – Control AI personality, tone, response style via pre-prompts
  • Visual theme editor – Real-time preview of branding changes
  • Domain allowlisting – Restrict embedding to approved sites only
Customization & Flexibility ( Behavior & Knowledge)
N/A
  • Add new sources, tweak retrieval, mix collections—everything’s programmable.
  • Chain API calls, re-rank docs, or build full agentic flows
  • Live content updates – Add/remove content with automatic re-indexing
  • System prompts – Shape agent behavior and voice through instructions
  • Multi-agent support – Different bots for different teams
  • Smart defaults – No ML expertise required for custom behavior
No- Code Interface & Usability
N/A
  • No no-code UI—built for devs to wire into their own front ends.
  • Dashboard is utilitarian: good for testing and monitoring, not for everyday business users.
  • 2-minute deployment – Fastest time-to-value in the industry
  • Wizard interface – Step-by-step with visual previews
  • Drag-and-drop – Upload files, paste URLs, connect cloud storage
  • In-browser testing – Test before deploying to production
  • Zero learning curve – Productive on day one
Competitive Positioning
N/A
  • Market position – Developer-first RAG infrastructure combining open-source flexibility with managed cloud service
  • Target customers – Dev teams needing high-performance RAG, enterprises requiring millions tokens/second ingestion
  • Key competitors – LangChain/LangSmith, Deepset/Haystack, Pinecone Assistant, custom RAG implementations
  • Competitive advantages – HybridRAG (150% accuracy boost), async auto-scaling, 40+ formats, sub-second latency
  • Pricing advantage – Free tier + $25/mo Dev plan; open-source foundation enables cost optimization
  • Use case fit – Massive document volumes, advanced RAG needs, self-hosting control requirements
  • Market position – Leading RAG platform balancing enterprise accuracy with no-code usability. Trusted by 6,000+ orgs including Adobe, MIT, Dropbox.
  • Key differentiators – #1 benchmarked accuracy • 1,400+ formats • Full white-labeling included • Flat-rate pricing
  • vs OpenAI – 10% lower hallucination, 13% higher accuracy, 34% faster
  • vs Botsonic/Chatbase – More file formats, source citations, no hidden costs
  • vs LangChain – Production-ready in 2 min vs weeks of development
R A G-as-a- Service Assessment
N/A
  • Platform Type – HYBRID RAG-AS-A-SERVICE combining open-source R2R with managed SciPhi Cloud
  • Core Mission – Bridge experimental RAG models to production-ready systems with deployment flexibility
  • Developer Target – Built for OSS community, startups, enterprises emphasizing developer flexibility and control
  • RAG Leadership – HybridRAG (150% accuracy), millions tokens/second, 40+ formats, sub-second latency
  • ✅ Open-source R2R core on GitHub enables customization, portability, avoids vendor lock-in
  • ⚠️ NO no-code features – No chat widgets, visual builders, pre-built integrations or dashboards
  • Platform type – TRUE RAG-AS-A-SERVICE with managed infrastructure
  • API-first – REST API, Python SDK, OpenAI compatibility, MCP Server
  • No-code option – 2-minute wizard deployment for non-developers
  • Hybrid positioning – Serves both dev teams (APIs) and business users (no-code)
  • Enterprise ready – SOC 2 Type II, GDPR, WCAG 2.0, flat-rate pricing

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Final Thoughts

Final Verdict: LiveChat vs SciPhi

After analyzing features, pricing, performance, and user feedback, both LiveChat and SciPhi are capable platforms that serve different market segments and use cases effectively.

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
  • Exceptional compliance portfolio: SOC 2 + GDPR + HIPAA + ISO 27001 + PCI DSS + FedRAMP + CSA Star Level 1

Best For: Mature 20+ year platform with proven enterprise reliability (Adobe, PayPal, IKEA, Samsung, Best Buy)

When to Choose SciPhi

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

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

Migration & Switching Considerations

Switching between LiveChat and SciPhi requires careful planning. Consider data export capabilities, API compatibility, and integration complexity. Both platforms offer migration support, but expect 2-4 weeks for complete transition including testing and team training.

Pricing Comparison Summary

LiveChat starts at $20/month, while SciPhi begins at custom pricing. Total cost of ownership should factor in implementation time, training requirements, API usage fees, and ongoing support. Enterprise deployments typically see annual costs ranging from $10,000 to $500,000+ depending on scale and requirements.

Our Recommendation Process

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

For most organizations, the decision between LiveChat and SciPhi comes down to specific requirements rather than overall superiority. Evaluate both platforms with your actual data during trial periods, focusing on accuracy, latency, ease of integration, and total cost of ownership.

📚 Next Steps

Ready to make your decision? We recommend starting with a hands-on evaluation of both platforms using your specific use case and data.

  • • Review: Check the detailed feature comparison table above
  • • Test: Sign up for free trials and test with real queries
  • • Calculate: Estimate your monthly costs based on expected usage
  • • Decide: Choose the platform that best aligns with your requirements

Last updated: February 24, 2026 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

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Priyansh Khodiyar's avatar

Priyansh Khodiyar

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

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