Data Ingestion & Knowledge Sources
100+ Native Connectors – SharePoint, Salesforce, ServiceNow, Confluence, databases, file shares, Slack, websites merged into one indexOCR & Structured Data – Indexes scanned docs, intranet pages, knowledge articles, multimedia contentReal-Time Sync – Incremental crawls, push APIs, scheduled syncs keep content fresh
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 archivesWebsite crawling – Sitemap indexing with configurable depth for help docs, FAQs, and public contentMultimedia transcription – AI Vision, OCR, YouTube/Vimeo/podcast speech-to-text built-inCloud integrations – Google Drive, SharePoint, OneDrive, Dropbox, Notion with auto-syncKnowledge platforms – Zendesk, Freshdesk, HubSpot, Confluence, Shopify connectorsMassive scale – 60M words (Standard) / 300M words (Premium) per bot with no performance degradation
Atomic UI Components – Drop-in components for search pages, support hubs, commerce sites with generative answersNative Platform Integrations – Salesforce, Sitecore with AI answers inside existing toolsREST APIs – Build custom chatbots, virtual assistants on Coveo's retrieval engine
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 positioningCMS plugins – WordPress, WIX, Webflow, Framer, SquareSpace native support5,000+ app ecosystem – Zapier connects CRMs, marketing, e-commerce toolsMCP Server – Integrate with Claude Desktop, Cursor, ChatGPT, WindsurfOpenAI SDK compatible – Drop-in replacement for OpenAI API endpointsLiveChat + Slack – Native chat widgets with human handoff capabilities
Uses Relevance Generative Answering (RGA)—a two-step retrieval plus LLM flow that produces concise, source-cited answers.
Respects permissions, showing each user only the content they’re allowed to see.
Blends the direct answer with classic search results so people can dig deeper if they want.
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
Atomic components are fully styleable with CSS, making it easy to match your brand’s look and feel.
You can tweak answer formatting and citation display through configs; deeper personality tweaks mean editing the prompt.
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 cost2-minute setup – No-code wizard with drag-and-drop interfacePersona customization – Control AI personality, tone, response style via pre-promptsVisual theme editor – Real-time preview of branding changesDomain allowlisting – Restrict embedding to approved sites only
Azure OpenAI GPT – Primary models via Azure OpenAI for high-quality generationBring Your Own LLM – Relevance-Augmented Passage Retrieval API supports custom modelsAuto-Tuning – Handles model tuning, prompt optimization; API override available
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 availableClaude 4.5 – Anthropic's Opus available for EnterpriseAuto model routing – Balances cost/performance automaticallyZero API key management – All models managed behind the scenes
Developer Experience ( A P I & S D Ks)
REST APIs & SDKs – Java, .NET, JavaScript for indexing, connectors, queryingUI Components – Atomic and Quantic components for fast front-end integrationEnterprise Documentation – Step-by-step guides for pipelines, index management
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 queriesPython SDK – Open-source customgpt-client with full API coveragePostman collections – Pre-built requests for rapid prototypingWebhooks – Real-time event notifications for conversations and leadsOpenAI compatible – Use existing OpenAI SDK code with minimal changes
Pairs keyword search with semantic vector search so the LLM gets the best possible context.
Reranking plus smart prompts keep hallucinations low and citations precise.
Built on a scalable architecture that handles heavy query loads and massive content sets.
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 cachingBenchmark-proven – 13% higher accuracy, 34% faster than OpenAI Assistants APIAnti-hallucination tech – Responses grounded only in your provided contentOpenGraph citations – Rich visual cards with titles, descriptions, images99.9% uptime – Auto-scaling infrastructure handles traffic spikes
Customization & Flexibility ( Behavior & Knowledge)
Fine-tune which sources and metadata the engine uses via query pipelines and filters.
Integrates with SSO/LDAP so results are tailored to each user’s permissions.
Developers can tweak prompt templates or inject business rules to shape the output.
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-indexingSystem prompts – Shape agent behavior and voice through instructionsMulti-agent support – Different bots for different teamsSmart defaults – No ML expertise required for custom behavior
Enterprise Licensing – Pricing based on sources, query volume, features99.999% Uptime – Scales to millions of queries, regional data centersAnnual Contracts – Volume tiers with optional premium support
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 botsPremium: $449/mo – 300M words, 100 botsAuto-scaling – Managed cloud scales with demandFlat rates – No per-query charges
ISO 27001/27018, SOC 2 – Plus HIPAA-compatible deployments availablePermission-Aware – Granular access controls, users see only authorized contentPrivate Cloud/On-Prem – Deployment options for strict data-residency requirements
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 complianceEncryption – 256-bit AES at rest, SSL/TLS in transitAccess controls – RBAC, 2FA, SSO, domain allowlistingData isolation – Never trains on your data
Observability & Monitoring
Analytics Dashboard – Tracks query volume, engagement, generative-answer performancePipeline Logs – Exportable for deeper analysis and troubleshootingA/B Testing – Query pipeline experiments to measure impact, fine-tune relevance
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 timesCustomer Intelligence – User behavior patterns, popular queries, knowledge gapsConversation analytics – Full transcripts, resolution rates, common questionsExport capabilities – API export to BI tools and data warehouses
Enterprise Support – Account managers, 24/7 help, extensive training programsPartner Network – Coveo Connect community with docs, forums, certified integrationsRegular Updates – Product releases and industry events for latest trends
Community help via Discord and GitHub; Enterprise customers get dedicated support
Open-source core encourages community contributions and integrations.
Comprehensive docs – Tutorials, cookbooks, API referencesEmail + in-app support – Under 24hr response timePremium support – Dedicated account managers for Premium/EnterpriseOpen-source SDK – Python SDK, Postman, GitHub examples5,000+ Zapier apps – CRMs, e-commerce, marketing integrations
Additional Considerations
Coveo goes beyond Q&A to power search, recommendations, and discovery for large digital experiences.
Deep integration with enterprise systems and strong permissioning make it ideal for internal knowledge management.
Feature-rich but best suited for organizations with an established IT team to tune and maintain it.
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 DIYAlways current – Auto-updates to latest GPT modelsProven scale – 6,000+ organizations, millions of queriesMulti-LLM – OpenAI + Claude reduces vendor lock-in
No- Code Interface & Usability
Admin Console – Atomic components enable minimal-code starts⚠️ Developer Involvement – Full generative setup requires technical resources
Best For – Teams with existing IT resources, more complex than pure no-code
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 industryWizard interface – Step-by-step with visual previewsDrag-and-drop – Upload files, paste URLs, connect cloud storageIn-browser testing – Test before deploying to productionZero learning curve – Productive on day one
Market Position – Enterprise AI-powered search/discovery with RGA for large-scale knowledge managementTarget Customers – Large enterprises with complex content (SharePoint, Salesforce, ServiceNow, Confluence) needing permission-aware searchKey Competitors – Azure AI Search, Vectara.ai, Glean, Elastic Enterprise SearchCompetitive Advantages – 100+ connectors, hybrid search, permission-aware results, 99.999% uptime SLAPricing – Enterprise licensing higher than SaaS chatbots; best value for unified search across massive contentUse Case Fit – Knowledge hubs, support portals, commerce sites with generative answers
Market position – Developer-first RAG infrastructure combining open-source flexibility with managed cloud serviceTarget customers – Dev teams needing high-performance RAG, enterprises requiring millions tokens/second ingestionKey competitors – LangChain/LangSmith, Deepset/Haystack, Pinecone Assistant, custom RAG implementationsCompetitive advantages – HybridRAG (150% accuracy boost), async auto-scaling, 40+ formats, sub-second latencyPricing advantage – Free tier + $25/mo Dev plan; open-source foundation enables cost optimizationUse 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 pricingvs OpenAI – 10% lower hallucination, 13% higher accuracy, 34% fastervs Botsonic/Chatbase – More file formats, source citations, no hidden costsvs LangChain – Production-ready in 2 min vs weeks of development
Azure OpenAI GPT – Primary models via Azure OpenAI for high-quality generationModel Flexibility – Relevance-Augmented Passage Retrieval API supports custom LLMsAuto-Tuning – Handles model tuning, prompt optimization automatically; API override availableSearch Integration – LLM tightly integrated with keyword + semantic search pipeline
LLM-Agnostic Architecture – GPT-4, GPT-3.5, Claude, Llama 2, and other open-source modelsModel Flexibility – Easy swapping to balance cost/performance without vendor lock-inCustom Support – Configure any LLM via API including fine-tuned or proprietary modelsEmbedding 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 seriesAnthropic – Claude 4.5 Opus/Sonnet (Enterprise)Auto-routing – Intelligent model selection for cost/performanceManaged – No API keys or fine-tuning required
RGA (Relevance Generative Answering) – Two-step retrieval + LLM producing source-cited answersHybrid Search – Keyword + semantic vector search for optimal LLM contextReranking & Smart Prompts – Keeps hallucinations low, citations precisePermission-Aware – SSO/LDAP integration shows only authorized content per userQuery Pipelines – Fine-tune sources, metadata, filters for retrieval control99.999% Uptime – Scalable architecture for heavy query loads, massive content sets
HybridRAG Technology – Vector search + knowledge graphs for 150% accuracy improvementHybrid Search – Dense vector + keyword with reciprocal rank fusionAgentic RAG – Reasoning agent for autonomous research across documents and webMultimodal 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 benchmarksAnti-hallucination – Responses grounded in your content onlyAutomatic citations – Clickable source links in every responseSub-second latency – Optimized vector search and cachingScale to 300M words – No performance degradation at scale
Industries – Financial Services, Telecommunications, High-Tech, Retail, Healthcare, ManufacturingInternal Knowledge – Enterprise systems integration, permissioning for documentation, knowledge hubsCustomer Support – Support hubs with generative answers from knowledge bases, ticket historyCommerce Sites – Product search, recommendations, AI-powered discovery featuresContent Scale – Large distributed content across SharePoint, databases, file shares, Confluence, ServiceNowTeam Sizes – Large enterprises with IT teams, millions of queries
Enterprise Knowledge – Process millions of documents with knowledge graph relationshipsSupport Automation – RAG-powered support bots with accurate, grounded responsesResearch & Analysis – Agentic RAG for autonomous research across collections and webCompliance & Legal – Large document repositories with precise citation trackingInternal Docs – Developer-focused RAG for code, API references, technical knowledgeCustom AI Apps – API-first architecture integrates into any application or workflow
Customer support – 24/7 AI handling common queries with citationsInternal knowledge – HR policies, onboarding, technical docsSales enablement – Product info, lead qualification, educationDocumentation – Help centers, FAQs with auto-crawlingE-commerce – Product recommendations, order assistance
ISO 27001/27018, SOC 2 – International security, privacy standards for enterprisesHIPAA-Compatible – Deployments available for healthcare compliance requirementsGranular Access Controls – Permission-aware search, SSO/LDAP integrationPrivate Cloud/On-Prem – Options for strict data-residency requirements99.999% Uptime SLA – Regional data centers for mission-critical infrastructure
Data Isolation – Single-tenant architecture with isolated customer data in SciPhi CloudSelf-Hosting Option – On-premise deployment for complete data control in regulated industriesEncryption Standards – TLS in transit, AES-256 at rest encryptionAccess 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 compliance256-bit AES encryption – Data at rest; SSL/TLS in transitSSO + 2FA + RBAC – Enterprise access controls with role-based permissionsData isolation – Never trains on customer dataDomain allowlisting – Restrict chatbot to approved domains
Enterprise Licensing – $600 to $1,320 depending on sources, query volume, featuresPro Plan – Entry-level with core search, RGA for smaller enterprisesEnterprise Plan – Full-featured with advanced capabilities, higher volumes, premium supportAnnual Contracts – Volume tiers with optional premium support packages⚠️ Consumption-Based – Pricing model can make costs hard to predict
Best Value For – Unified search across massive content, millions of queries
Free Tier – Generous no-credit-card tier for experimentation and developmentDeveloper Plan – $25/month for individual developers and small projectsEnterprise Plans – Custom pricing based on scale, features, and supportSelf-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/botPremium: $449/mo – 100 chatbots, 300M words, 20K items/botEnterprise: Custom – SSO, dedicated support, custom SLAs7-day free trial – Full Standard access, no chargesFlat-rate pricing – No per-query charges, no hidden costs
Enterprise Support – Account managers, 24/7 help, guaranteed response timesPartner Network – Certified integrations via Coveo Connect communityDocumentation – Step-by-step guides for pipelines, index management, connectorsTraining Programs – Admin console, Atomic components, developer integrationRegular Updates – Product releases, industry events for latest trends
Comprehensive Docs – Detailed docs at r2r-docs.sciphi.ai covering all features and endpointsGitHub Repository – Active open-source development at github.com/SciPhi-AI/R2R with code examplesCommunity Support – Discord community and GitHub issues for peer supportEnterprise 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 referencesSupport channels – Email, in-app chat, dedicated managers (Premium+)Open-source – Python SDK, Postman, GitHub examplesCommunity – User community + 5,000 Zapier integrations
Limitations & Considerations
⚠️ Developer Involvement – Full generative setup requires technical resources
⚠️ Cost Predictability – Consumption-based pricing hard to predict for enterprise scale
⚠️ IT Team Needed – Best for organizations with established technical teams
⚠️ Enterprise Focus – Optimized for enterprises vs. SMBs or startups
NOT Ideal For – Small businesses, plug-and-play chatbot needs, immediate no-code deployment
⚠️ 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-ownModel selection – OpenAI + Anthropic only; no Cohere, AI21, open-sourceReal-time data – Requires re-indexing; not ideal for live inventory/pricesEnterprise features – Custom SSO only on Enterprise plan
Agentic AI Integration – Coveo for Agentforce, expanded API suite, Design Partner Program (2024-2025)Agent API Suite – Search API, Passage Retrieval API, Answer API for grounding agentsSalesforce Agentforce – Native integration for customer service, sales, marketing agentsAWS RAG-as-a-Service – MCP Server for Amazon Bedrock AgentCore, Agents, Quick Suite (Dec 2024)Four Tools – Passage Retrieval, Answer gen (Amazon Nova), Search, FetchSecurity-First – Inherits document/item-level permissions automatically for trusted answers
Agentic RAG – Reasoning agent for autonomous research across documents/web with multi-step problem solvingAdvanced Toolset – Semantic search, metadata search, document retrieval, web search, web scraping capabilitiesMulti-Turn Context – Stateful dialogues maintaining conversation history via conversation_id for follow-upsCitation 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 tasksMulti-Agent Systems – Specialized agents for support, sales, knowledgeMemory & Context – Persistent conversation history across sessionsTool Integration – Webhooks + 5,000 Zapier apps for automationContinuous Learning – Auto re-indexing without manual retraining
R A G-as-a- Service Assessment
Platform Type – Enterprise search with RAG-as-a-Service, Relevance Generative Answering (RGA)RAG Launch – AWS RAG-as-a-Service announced December 1, 2024 as cloud-native offering40% Accuracy Improvement – RAG increases base model accuracy according to industry studiesHybrid Search – Keyword, vector, hybrid search with relevance tuning100+ Connectors – SharePoint, Salesforce, ServiceNow, Confluence, databases, SlackBest For – Enterprises with distributed content needing permission-aware search, knowledge hubs, generative answers
Platform Type – HYBRID RAG-AS-A-SERVICE combining open-source R2R with managed SciPhi CloudCore Mission – Bridge experimental RAG models to production-ready systems with deployment flexibilityDeveloper Target – Built for OSS community, startups, enterprises emphasizing developer flexibility and controlRAG 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 infrastructureAPI-first – REST API, Python SDK, OpenAI compatibility, MCP ServerNo-code option – 2-minute wizard deployment for non-developersHybrid 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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