Data Ingestion & Knowledge Sources
Document support – PDF, DOCX, HTML automatically indexed (Vectara Platform )Auto-sync connectors – Cloud storage and enterprise system integrations keep data currentEmbedding processing – Background conversion to embeddings enables fast semantic search
Knowledge Base (KB) – RAG-powered retrieval: PDF, Word, CSV, plain text uploadsWebsite crawling – Sitemap ingestion, auto-sync Google Drive, Notion, Confluence, Zendesk (Pro+)✅ No explicit document limits, scales by storage tier
⚠️ Accuracy concerns – Reviews cite KB "often inaccurate" and "too general"
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
REST APIs & SDKs – Easy integration into custom applications with comprehensive toolingEmbedded experiences – Search/chat widgets for websites, mobile apps, custom portalsLow-code connectors – Azure Logic Apps and PowerApps simplify workflow integration
15+ native integrations – Zendesk, Salesforce, HubSpot, Intercom, Slack, Teams, FreshdeskMessaging & voice – WhatsApp, SMS, Alexa, Google Assistant, custom telephonyE-commerce – Shopify, Stripe, Zapier, Make.com (5000+ apps), Calendly✅ Custom integrations via unlimited HTTP API blocks, webhooks, iOS/Android SDKs
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
Vector + LLM search – Smart retrieval with generative answers, context-aware responsesMockingbird LLM – Proprietary model with source citations (details )Multi-turn conversations – Conversation history tracking for smooth back-and-forth dialogue
Visual workflow canvas – 50+ drag-and-drop blocks (text, cards, buttons, forms, APIs)Multi-turn conversations – Context preservation across sessions with full transcript loggingAgent handoff – Multi-agent routing, human handoff with context transfer100+ languages – Intent recognition, entity extraction, slot filling via NLU✅ Analytics dashboard: sessions, users, completion rates, drop-offs, A/B testing
✅ #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
White-label control – Full theming, logos, CSS customization for brand alignmentDomain restrictions – Bot scope and branding configurable per deploymentSearch UI styling – Result cards and search interface match company identity
Visual widget editor – Custom colors, logos, fonts, button styles, bubble positioningWhite-labeling – Remove branding (Team+), custom domains (Pro+), CSS injection✅ Dynamic personalization via user attributes, multi-channel customization, configurable tone/prompts
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
Mockingbird default – In-house model with GPT-4/GPT-3.5 via Azure OpenAI availableFlexible selection – Choose model balancing cost versus quality for use caseCustom prompts – Prompt templates configurable for tone, format, citation rules
Multi-model support – GPT-4, GPT-3.5, Claude, Gemini per agent/step configurationFunction calling – GPT-4/Claude support with custom model API integrationPrompt controls – System prompts, few-shot examples, temperature/token controls per request✅ Cost optimization via model routing, RAG auto-augments LLM prompts
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)
Multi-language SDKs – C#, Python, Java, JavaScript with REST API (FAQs )Clear documentation – Sample code and guides for integration, indexing operationsSecure authentication – Azure AD or custom auth setup for API access
REST API & SDKs – JavaScript/TypeScript, Python, GraphQL API for queriesAPI capabilities – Send messages, manage state, retrieve transcripts, update KBCustom code blocks – JavaScript execution within workflows, rate limits 10K/hour (Pro)✅ Comprehensive docs, 15K+ community (Discord/Slack), Postman/OpenAPI specs
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
✅ Enterprise scale – Millisecond responses with heavy traffic (benchmarks )✅ Hybrid search – Semantic and keyword matching for pinpoint accuracy✅ Hallucination prevention – Advanced reranking with factual-consistency scoring
Response times – 200-500ms simple, 1-2s complex; 99.9% SLA (Enterprise)Accuracy claims – GoStudent case: 98% accuracy on 100K conversationsHallucination prevention – RAG grounding, confidence thresholds, source citations⚠️ KB accuracy concerns – Reviews cite "often inaccurate", manual preprocessing required
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)
Indexing control – Configure chunk sizes, metadata tags, retrieval parametersSearch weighting – Tune semantic vs lexical search balance per queryDomain tuning – Adjust prompt templates and relevance thresholds for specialty domains
Real-time updates – Workflow changes deploy instantly, no rebuild requiredVersion control – Git-style versioning, rollback, Dev/Staging/Prod environments (Team+)Component reusability – Save sections, 100+ templates, dynamic KB syncing✅ Task-specific flows, multi-language routing, user segmentation by custom attributes
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
Usage-based pricing – Free tier available, bundles scale with growth (pricing )Enterprise tiers – Plans scale with query volume, data size for heavy usageDedicated deployment – VPC or on-prem options for data isolation requirements
Sandbox (Free) – 2 agents, unlimited interactions, 3 collaboratorsPro: $50/month – 10 agents, unlimited interactions, 10 collaboratorsTeam: $625/month – 50 agents, 25 collaborators, API, version control, RBACEnterprise: Custom – Unlimited agents, SSO, SOC 2, SLA, dedicated support⚠️ Pricing complexity – Per-seat ($15-25) + per-agent ($20-50) charges escalate quickly
Standard: $99/mo – 60M words, 10 botsPremium: $449/mo – 300M words, 100 botsAuto-scaling – Managed cloud scales with demandFlat rates – No per-query charges
✅ Data encryption – Transit and rest encryption, no model training on your content✅ Compliance certifications – SOC 2, ISO, GDPR, HIPAA (details )✅ Customer-managed keys – BYOK support with private deployments for full control
SOC 2 Type II certified – GDPR compliant, HIPAA ready (Enterprise)Encryption – AES-256 at rest, TLS 1.3 in transit, zero-retention policySSO/SAML – Okta/Azure AD, RBAC (Team+), audit logs (Enterprise)✅ On-premise deployment, EU data residency, DPA, IP whitelisting, key rotation
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
Azure portal dashboard – Query latency, index health, usage metrics at-a-glanceAzure Monitor integration – Azure Monitor and App Insights for custom alertsAPI log exports – Metrics exportable via API for compliance, analysis reports
Analytics dashboard – Sessions, users, messages, completion rates, drop-off visualizationConversation funnels – Journey mapping with full transcript viewerError tracking – Monitor API failures, timeouts, unhandled intents real-time✅ User feedback (thumbs/CSAT/NPS), CSV/JSON export, Datadog/New Relic webhooks
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
Microsoft network – Comprehensive docs, forums, technical guides backed by MicrosoftEnterprise support – Dedicated channels and SLA-backed help for enterprise plansAzure ecosystem – Broad partner network and active developer community access
Founded 2017 – $28M funding (Felicis, OpenAI Startup Fund, Tiger Global)200K+ teams – Mercedes-Benz, JP Morgan, Shopify; 15K+ developer communitySupport tiers – Community (Free), priority email (Pro), chat (Team), 24/7 CSM (Enterprise)✅ 100+ templates, Academy certifications, comprehensive docs, partner program
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
✅ Factual scoring – Hybrid search with reranking provides unique factual-consistency scoresFlexible deployment – Public cloud, VPC, or on-prem for varied compliance needsActive development – Regular feature releases and integrations keep platform current
Workflow-first platform – Excels complex workflows, KB accuracy lags RAG specialistsBest use case – Multi-step API orchestration, team collaboration; NOT document Q&A⚠️ Steep learning curve – Weeks onboarding despite visual interface
⚠️ Visual canvas overwhelm – Complex agents (100+ blocks) difficult to manage
⚠️ Pricing escalation – Per-seat/agent fees escalate beyond base costs quickly
⚠️ SOC 2 Enterprise-only – No SLA guarantees on lower tiers
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
Azure portal UI – Straightforward index management and settings configuration interfaceLow-code options – PowerApps, Logic Apps connectors enable quick non-dev integration⚠️ Technical complexity – Advanced indexing tweaks require developer expertise vs turnkey tools
Visual canvas builder – Drag-and-drop 50+ blocks, 80% no-code coverageCollaboration – 10+ simultaneous editors, real-time cursor tracking, commentsTesting tools – Built-in chat simulator, one-click channel deployment✅ Ease of use 8.7/10 (G2), 100+ templates, Academy certifications
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 RAG platform between Azure AI Search and chatbot buildersTarget customers – Enterprises needing production RAG, white-label APIs, VPC/on-prem deploymentsKey competitors – Azure AI Search, Coveo, OpenAI Enterprise, Pinecone AssistantCompetitive advantages – Mockingbird LLM, hallucination detection, SOC 2/HIPAA compliance, millisecond responsesPricing advantage – Usage-based with free tier, best value for enterprise RAG infrastructureUse case fit – Mission-critical RAG, white-label APIs, Azure integration, high-accuracy requirements
Market position – Workflow-first platform (founded 2017, $28M funding) for orchestrationTarget customers – Enterprise teams (200K+ users: Mercedes-Benz, JP Morgan) needing multi-agent workflowsKey competitors – Botpress, Rasa, Microsoft Power Virtual Agents, NOT RAG toolsCompetitive advantages – 50+ blocks, 10+ real-time collab, 15+ integrations, SOC 2/GDPR/HIPAA✅ Free Sandbox, Pro $50/month reasonable for startups, best for workflows
⚠️ Use case fit – Ideal complex workflows, NOT simple document Q&A
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
✅ Mockingbird LLM – 26% better than GPT-4 on BERT F1, 0.9% hallucination rate✅ Mockingbird 2 – 7 languages (EN/ES/FR/AR/ZH/JA/KO), under 10B parametersGPT-4/GPT-3.5 fallback – Azure OpenAI integration for OpenAI model preferenceHHEM + HCM – Hughes Hallucination Evaluation with Correction Model (Mockingbird-2-Echo)✅ No training on data – Customer data never used for model training/improvementCustom prompts – Templates configurable for tone, format, citation rules per domain
Multi-model support – GPT-4, GPT-3.5, Claude, Gemini per agent/step selectionFunction calling – GPT-4/Claude real-time action triggering during conversationsCustom model integration – Proprietary LLM API support, temperature/token controls (0.0-2.0)✅ Cost optimization routing: GPT-3.5 simple, GPT-4 complex queries
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
✅ Hybrid search – Semantic vector + BM25 keyword matching for pinpoint accuracy✅ Advanced reranking – Multi-stage pipeline optimizes results before generation with relevance scoring✅ Factual scoring – HHEM provides reliability score for every response's grounding quality✅ Citation precision – Mockingbird outperforms GPT-4 on citation metrics, traceable to sourcesMultilingual RAG – Cross-lingual: query/retrieve/generate in different languages (7 supported)Structured outputs – Extract specific information for autonomous agent integration, deterministic data
Knowledge Base – RAG vector search, semantic matching (PDF, Word, CSV, text)Website crawling – Sitemap ingestion, auto-sync Google Drive, Notion, Confluence, ZendeskMulti-turn context – Conversation preservation across sessions for coherent dialogues⚠️ Accuracy concerns – Reviews cite KB "often inaccurate", "too general"
⚠️ No RAG controls – Cannot configure chunking, embeddings, similarity thresholds
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
Regulated industries – Health, legal, finance needing accuracy, security, SOC 2 complianceEnterprise knowledge – Q&A systems with precise answers from large document repositoriesAutonomous agents – Structured outputs for deterministic data extraction, decision-making workflowsWhite-label APIs – Customer-facing search/chat with millisecond responses at enterprise scaleMultilingual support – 7 languages with single knowledge base for multiple localesHigh accuracy needs – Citation precision, factual scoring, 0.9% hallucination rate (Mockingbird-2-Echo)
Complex workflows – API orchestration, multi-agent coordination, sophisticated logicTeam collaboration – 10+ simultaneous editors with real-time tracking/commentsVoice assistants – Alexa, Google Assistant, custom telephony conversational AICustomer service – 15+ integrations (Zendesk, Salesforce, HubSpot, Intercom) automationE-commerce – Shopify orders, product recommendations, lead gen with Calendly/CRM⚠️ NOT ideal for – Simple document Q&A (KB accuracy issues)
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
✅ SOC 2 Type 2 – Independent audit demonstrating enterprise-grade operational security controls✅ ISO 27001 + GDPR – Information security management with EU data protection compliance✅ HIPAA ready – Healthcare compliance with BAAs available for PHI handling✅ Encryption – TLS 1.3 in transit, AES-256 at rest with BYOK support✅ Zero data retention – No model training on customer data, content stays privatePrivate deployments – VPC or on-premise for data sovereignty and network isolation
SOC 2 Type II – GDPR compliant, HIPAA ready (Enterprise), EU data residencyEncryption – AES-256 at rest, TLS 1.3 in transit, zero-retentionSSO/SAML – Okta, Azure AD, OneLogin; RBAC (Team+), audit logs (Enterprise)✅ On-premise deployment for data sovereignty, DPA available
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
30-day free trial – Full enterprise feature access for evaluation before commitmentUsage-based pricing – Pay for query volume and data size with scalable tiersFree tier – Generous free tier for development, prototyping, small production deploymentsEnterprise pricing – Custom pricing for VPC/on-prem installations, heavy usage bundles available✅ Transparent pricing – No per-seat charges, storage surprises, or model switching feesFunding – $53.5M raised ($25M Series A July 2024, FPV/Race Capital)
Sandbox (Free) – 2 agents, unlimited interactions, 3 collaboratorsPro: $50/month – 10 agents, unlimited interactions, 10 collaborators, GPT-4/ClaudeTeam: $625/month – 50 agents, 25 collaborators, API, version control, RBACEnterprise: Custom – Unlimited agents, SSO, SOC 2, HIPAA, SLA, on-premise⚠️ Per-seat charges – Additional editors $50/month (Pro), $15-25/month (Team)
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 – Dedicated channels and SLA-backed help for enterprise customersMicrosoft network – Extensive infrastructure, forums, technical guides backed by MicrosoftComprehensive docs – API references, integration guides, SDKs at docs.vectara.comSample code – Pre-built examples, Jupyter notebooks, quick-start guides for rapid integrationActive community – Developer forums for peer support, knowledge sharing, best practices
Founded 2017 – $28M funding (Felicis, OpenAI Startup Fund, Tiger Global)200K+ teams – Mercedes-Benz, JP Morgan, Shopify; 15K+ developer communitySupport tiers – Community (Free), priority email (Pro), chat (Team), 24/7 CSM (Enterprise)✅ 100+ templates, comprehensive docs, Academy certifications, partner program
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
⚠️ Azure ecosystem focus – Best with Azure services, less smooth for AWS/GCP organizations⚠️ Developer expertise needed – Advanced indexing requires technical skills vs turnkey no-code tools⚠️ No drag-and-drop GUI – Azure portal management but no chatbot builder like Tidio/WonderChat⚠️ Limited model selection – Mockingbird/GPT-4/GPT-3.5 only, no Claude/Gemini/custom models⚠️ Sales-driven pricing – Contact sales for enterprise pricing, less transparent than self-serve platforms⚠️ Overkill for simple bots – Enterprise RAG unnecessary for basic FAQ or customer service
⚠️ KB accuracy issues – Reviews cite "often inaccurate", not ideal document Q&A
⚠️ Workflow-first platform – Excels orchestration, lags specialized RAG platforms
⚠️ Steep learning curve – Weeks onboarding despite visual interface
⚠️ Pricing complexity – Per-seat/agent fees escalate beyond base costs
⚠️ Visual canvas overwhelm – Complex agents (100+ blocks) difficult to manage
⚠️ SOC 2 Enterprise-only – No SLA guarantees on Pro/Team tiers
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 RAG Framework – Python library for autonomous agents: emails, bookings, system integrationAgent APIs (Tech Preview) – Customizable reasoning models, behavioral instructions, tool access controlsLlamaIndex integration – Rapid tool creation connecting Vectara corpora, single-line code generationMulti-LLM support – OpenAI, Anthropic, Gemini, GROQ, Together.AI, Cohere, AWS Bedrock integrationStep-level audit trails – Source citations, reasoning steps, decision paths for governance compliance✅ Grounded actions – Document-grounded decisions with citations, 0.9% hallucination rate (Mockingbird-2-Echo)⚠️ Developer platform – Requires programming expertise, not for non-technical teams⚠️ No chatbot UI – No polished widgets or turnkey conversational interfaces⚠️ Tech preview status – Agent APIs subject to change before general availability
Agent step (2024) – Autonomous AI with tool use, decision-making, KB accessMulti-agent orchestration – Supervisor pattern connecting specialized agents for conversation aspectsHybrid architecture – Hard business logic + Agent networks for flexibilityHuman handoff – Smooth transitions with full history transfer to support/salesLead capture & CRM – Auto-create in HubSpot/Salesforce/Pipedrive, update deal stages
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 – TRUE ENTERPRISE RAG-AS-A-SERVICE: Agent OS for trusted AICore Mission – Deploy AI assistants/agents with grounded answers, safe actions, always-on governanceTarget Market – Enterprises needing production RAG, white-label APIs, VPC/on-prem deploymentsRAG Implementation – Mockingbird LLM (26% better than GPT-4), hybrid search, multi-stage rerankingAPI-First Architecture – REST APIs, SDKs (C#/Python/Java/JS), Azure integration (Logic Apps/Power BI)Security & Compliance – SOC 2 Type 2, ISO 27001, GDPR, HIPAA, BYOK, VPC/on-premAgent-Ready Platform – Python library, Agent APIs, structured outputs, audit trails, policy enforcementAdvanced RAG Features – Hybrid search, reranking, HHEM scoring, multilingual retrieval (7 languages)Funding – $53.5M raised ($25M Series A July 2024, FPV/Race Capital)⚠️ Enterprise complexity – Requires developer expertise for indexing, tuning, agent configuration⚠️ No no-code builder – Azure portal management but no drag-and-drop chatbot builder⚠️ Azure ecosystem focus – Best with Azure, less smooth for AWS/GCP cross-cloud flexibilityUse Case Fit – Mission-critical RAG, regulated industries (SOC 2/HIPAA), white-label APIs, VPC/on-prem
Platform Type – WORKFLOW-FIRST with RAG capabilities, NOT pure RAG-as-a-ServiceCore Architecture – Visual canvas (50+ blocks) combining intent-based + RAG hybridRAG Integration – KB with vector search (Qdrant) + GPT-4, secondary to workflowsDeveloper Experience – REST API, JS/Python SDKs, custom code blocks, GraphQL⚠️ RAG Limitations – KB "often inaccurate", no RAG parameter configuration, manual preprocessing
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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