Data Ingestion & Knowledge Sources
100+ Prebuilt Connectors – Google Drive, Slack, Salesforce, GitHub, Pinecone, Qdrant, MongoDB Atlas
Multimodal Embed v4.0 – Text + images in single vectors, 96 images/batch processing
Binary Embeddings – 8x storage reduction (1024 dim → 128 bytes)
⚠️ NO Native Cloud UI – Connectors require developer setup, not drag-and-drop
Document support – PDF, DOCX, HTML automatically indexed (Vectara Platform )
Auto-sync connectors – Cloud storage and enterprise system integrations keep data current
Embedding processing – Background conversion to embeddings enables fast semantic search
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
Developer Frameworks – LangChain, LlamaIndex, Haystack, Zapier (8,000+ apps)
Multi-Cloud Deployment – AWS Bedrock, Azure, GCP, Oracle OCI, cloud-agnostic portability
Cohere Toolkit – Open-source (3,150+ GitHub stars) Next.js deployment app
⚠️ NO Native Messaging/Widget – NO Slack, WhatsApp, Teams, embeddable chat requires custom development
REST APIs & SDKs – Easy integration into custom applications with comprehensive tooling
Embedded experiences – Search/chat widgets for websites, mobile apps, custom portals
Low-code connectors – Azure Logic Apps and PowerApps simplify workflow integration
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
North Platform (GA Aug 2025) – Customizable agents for HR, finance, IT with MCP
Grounded Generation – Inline citations showing exact document spans with hallucination reduction
Multi-Step Tool Use – Command models execute parallel tool calls with reasoning
⚠️ NO Lead Capture/Analytics – Must implement at application layer, no marketing automation
Agentic RAG Framework – Python library for autonomous agents: emails, bookings, system integration
Agent APIs (Tech Preview) – Customizable reasoning models, behavioral instructions, tool access controls
LlamaIndex integration – Rapid tool creation connecting Vectara corpora, single-line code generation
Multi-LLM support – OpenAI, Anthropic, Gemini, GROQ, Together.AI, Cohere, AWS Bedrock integration
Step-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
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
Open-Source Toolkit (MIT) – Complete frontend source code for unlimited customization
Fine-Tuning via LoRA – Command R models with 16K training context for specialization
White-Labeling – Fully supported via self-hosted deployments, NO Cohere branding
⚠️ NO Visual Agent Builder – Agent creation requires Python SDK, not for non-technical users
White-label control – Full theming, logos, CSS customization for brand alignment
Domain restrictions – Bot scope and branding configurable per deployment
Search UI styling – Result cards and search interface match company identity
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
Command A – 256K context, $2.50/$10, 75% faster than GPT-4o, 2-GPU minimum
Command R+ – 128K context, $2.50/$10, 50% higher throughput, 20% lower latency
Command R – 128K context, $0.15/$0.60, 66x cheaper than Command A output
Command R7B – 128K context, $0.0375/$0.15, fastest and lowest cost
23 Optimized Languages – English, French, Spanish, German, Japanese, Korean, Chinese, Arabic
Mockingbird default – In-house model with GPT-4/GPT-3.5 via Azure OpenAI available
Flexible selection – Choose model balancing cost versus quality for use case
Custom prompts – Prompt templates configurable for tone, format, citation rules
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)
Four Official SDKs – Python, TypeScript/JS, Java, Go with multi-cloud support
REST API v2 – Chat, Embed, Rerank, Classify, Tokenize, Fine-tuning, streaming
Native RAG – documents parameter for grounded generation with inline citations
LLM University (LLMU) – Learning paths for fundamentals, embeddings, SageMaker deployment
Multi-language SDKs – C#, Python, Java, JavaScript with REST API (FAQs )
Clear documentation – Sample code and guides for integration, indexing operations
Secure authentication – Azure AD or custom auth setup for API access
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
Command A Performance – 75% faster than GPT-4o, runs on 2 GPUs
Embed v3.0 Benchmarks – MTEB 64.5, BEIR 55.9 among 90+ models
Rerank 3.5 Context – 128K token window handles documents, emails, tables, code
Grounded Generation – Inline citations show exact document spans, reduces hallucination
✅ 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
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
Trial/Free – 20 chat/min, 1,000 calls/month for evaluation
Production Pay-Per-Token – Command A $2.50/$10, R7B $0.0375/$0.15 (66x cheaper output)
Production Unlimited Monthly – No monthly caps, 500 chat/min rate limit
Usage-based pricing – Free tier available, bundles scale with growth (pricing )
Enterprise tiers – Plans scale with query volume, data size for heavy usage
Dedicated deployment – VPC or on-prem options for data isolation requirements
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
SOC 2 Type II + ISO 27001 + ISO 42001 – Annual audits, AI Management certification
GDPR + CCPA Compliant – Data Processing Addendums, EU data residency
Zero Data Retention (ZDR) – Available upon approval, 30-day auto deletion
Air-Gapped Deployment – Full private on-premise, ZERO Cohere infrastructure access
⚠️ NO HIPAA Certification – Healthcare PHI processing requires sales verification
✅ 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 + 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
Observability & Monitoring
Native Dashboard – Billing/usage tracking, API key management, spending limits, tokens
North Platform – Audit-ready logs, traceability for enterprise compliance
Third-Party Integrations – Dynatrace, PostHog, New Relic, Grafana monitoring
⚠️ NO Native Real-Time Alerts – Proactive monitoring requires external integrations
Azure portal dashboard – Query latency, index health, usage metrics at-a-glance
Azure Monitor integration – Azure Monitor and App Insights for custom alerts
API log exports – Metrics exportable via API for compliance, analysis reports
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
Discord Community – 21,691+ members for API discussions, troubleshooting, Maker Spotlight
Cohere Labs – 4,500+ research community, 100+ publications including Aya (101 languages)
Interactive Documentation – docs.cohere.com with 'Try it' testing, Playground export
Enterprise Support – Dedicated account management, custom deployment, bespoke pricing
⚠️ NO Live Chat/Phone – Standard customers use Discord and email only
Microsoft network – Comprehensive docs, forums, technical guides backed by Microsoft
Enterprise support – Dedicated channels and SLA-backed help for enterprise plans
Azure ecosystem – Broad partner network and active developer community access
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
No- Code Interface & Usability
Playground – Visual model testing with parameter tuning, SDK code export
Dataset Upload UI – No-code dataset upload for fine-tuning via dashboard
⚠️ NO Visual Agent Builder – Agent creation requires Python SDK, not for non-technical users
Azure portal UI – Straightforward index management and settings configuration interface
Low-code options – PowerApps, Logic Apps connectors enable quick non-dev integration
⚠️ Technical complexity – Advanced indexing tweaks require developer expertise vs turnkey tools
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
Enterprise Deployment Flexibility ( Core Differentiator)
SaaS (Instant) – Immediate setup via Cohere API with global infrastructure
Multi-Cloud Support – AWS Bedrock, Azure, GCP, Oracle OCI, cloud-agnostic portability
VPC Deployment – <1 day setup within customer private cloud for isolation
Air-Gapped/On-Premises – Full private deployment, ZERO Cohere data access
✅ Unmatched Among Providers – OpenAI, Anthropic, Google lack comparable on-premise options
N/A
N/A
Grounded Generation with Citations ( Core Differentiator)
Inline Citations – Responses show exact document spans informing each answer
Fine-Grained Attribution – Citations link specific sentences/paragraphs vs generic references
Rerank 3.5 Integration – 128K context filters emails, tables, JSON to passages
Native RAG API – documents parameter enables grounded generation without external orchestration
✅ Competitive Advantage – Most platforms need custom citation, Cohere provides built-in
N/A
N/A
Multimodal Embed v4.0 ( Differentiator)
Text + Images – Single vectors combining text/images eliminate extraction pipelines
96 Images Per Batch – Embed Jobs API handles large-scale multimodal processing
Matryoshka Learning – Flexible dimensionality (256/512/1024/1536) for cost-performance optimization
Binary Embeddings – 8x storage reduction for large vector databases, minimal loss
✅ Top-Tier Benchmarks – MTEB 64.5, BEIR 55.9 among 90+ models
N/A
N/A
Command A – 23 optimized languages: English, French, Spanish, German, Japanese, Korean, Chinese
Embed and Rerank – 100+ languages with cross-lingual retrieval, no translation
Aya Research Model – Cohere Labs open research covering 101 languages
N/A
N/A
R A G-as-a- Service Assessment
Platform Type – TRUE RAG-AS-A-SERVICE API PLATFORM for custom developer solutions
API-First Architecture – REST API v2 + 4 SDKs (Python, TypeScript, Java, Go)
RAG Technology Leadership – Embed v4.0 (multimodal), Rerank 3.5 (128K), inline citations
Deployment Flexibility – SaaS, VPC, air-gapped on-premise, unmatched among major providers
⚠️ CRITICAL GAPS – NO chat widgets, messaging integrations, visual builders, analytics
Platform Type – TRUE ENTERPRISE RAG-AS-A-SERVICE: Agent OS for trusted AI
Core Mission – Deploy AI assistants/agents with grounded answers, safe actions, always-on governance
Target Market – Enterprises needing production RAG, white-label APIs, VPC/on-prem deployments
RAG Implementation – Mockingbird LLM (26% better than GPT-4), hybrid search, multi-stage reranking
API-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-prem
Agent-Ready Platform – Python library, Agent APIs, structured outputs, audit trails, policy enforcement
Advanced 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 flexibility
Use Case Fit – Mission-critical RAG, regulated industries (SOC 2/HIPAA), white-label APIs, VPC/on-prem
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
Market Position – Enterprise-first RAG API platform with unmatched deployment flexibility
Deployment Differentiator – Air-gapped on-premise, ZERO Cohere access vs SaaS-only competitors
Security Leadership – SOC 2 + ISO 27001 + ISO 42001 (rare AI certification) + GDPR
Cost Optimization – Command R7B 66x cheaper than A, model-to-use-case matching
Research Pedigree – Founded by Transformer co-author Gomez, $1.54B funding (RBC, Dell, Oracle)
Market position – Enterprise RAG platform between Azure AI Search and chatbot builders
Target customers – Enterprises needing production RAG, white-label APIs, VPC/on-prem deployments
Key competitors – Azure AI Search, Coveo, OpenAI Enterprise, Pinecone Assistant
Competitive advantages – Mockingbird LLM, hallucination detection, SOC 2/HIPAA compliance, millisecond responses
Pricing advantage – Usage-based with free tier, best value for enterprise RAG infrastructure
Use case fit – Mission-critical RAG, white-label APIs, Azure integration, high-accuracy 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
Customer Base & Case Studies
Financial Services – RBC (Royal Bank of Canada) for banking knowledge and compliance
Enterprise IT – Dell for knowledge management, Oracle for database docs
Global Operations – LG Electronics using multilingual capabilities for global operations
$1.54B Funding – Nvidia, Salesforce, Oracle, AMD, Schroders, Fujitsu investments
N/A
N/A
Command A – 256K context, $2.50/$10, 75% faster than GPT-4o
Command R+/R/R7B – 128K context, pricing from $0.0375 to $10 per 1M
66x Cost Difference – Command R7B output 66x cheaper than Command A
23 Optimized Languages – English, French, Spanish, German, Japanese, Korean, Chinese, Arabic
✅ 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 parameters
GPT-4/GPT-3.5 fallback – Azure OpenAI integration for OpenAI model preference
HHEM + HCM – Hughes Hallucination Evaluation with Correction Model (Mockingbird-2-Echo)
✅ No training on data – Customer data never used for model training/improvement
Custom prompts – Templates configurable for tone, format, citation rules per domain
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
Grounded Generation Built-In – Native documents parameter with fine-grained inline citations
Embed v4.0 Multimodal – Text + images in single vectors, 96 images/batch
Top-Tier Embeddings – MTEB 64.5, BEIR 55.9, Matryoshka (256/512/1024/1536 dim)
Rerank 3.5 – 128K token context handles documents, emails, tables, JSON, code
Binary Embeddings – 8x storage reduction (1024 dim → 128 bytes) minimal loss
✅ 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 sources
Multilingual RAG – Cross-lingual: query/retrieve/generate in different languages (7 supported)
Structured outputs – Extract specific information for autonomous agent integration, deterministic data
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
Financial Services – RBC deployment for banking knowledge, compliance, North for Banking
Healthcare – Ensemble Health for clinical knowledge (HIPAA verification required)
Enterprise IT – Dell for knowledge management, customer support, documentation search
Technology Companies – Oracle (database docs), LG Electronics (multilingual operations)
Regulated industries – Health, legal, finance needing accuracy, security, SOC 2 compliance
Enterprise knowledge – Q&A systems with precise answers from large document repositories
Autonomous agents – Structured outputs for deterministic data extraction, decision-making workflows
White-label APIs – Customer-facing search/chat with millisecond responses at enterprise scale
Multilingual support – 7 languages with single knowledge base for multiple locales
High accuracy needs – Citation precision, factual scoring, 0.9% hallucination rate (Mockingbird-2-Echo)
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
Free Tier – Trial API key with 20 chat/min, 1,000 calls/month
Production Pay-Per-Token – Command A $2.50/$10, R7B $0.0375/$0.15 (66x cheaper output)
Production Unlimited Monthly – No monthly caps, 500 chat/min rate limit
30-day free trial – Full enterprise feature access for evaluation before commitment
Usage-based pricing – Pay for query volume and data size with scalable tiers
Free tier – Generous free tier for development, prototyping, small production deployments
Enterprise pricing – Custom pricing for VPC/on-prem installations, heavy usage bundles available
✅ Transparent pricing – No per-seat charges, storage surprises, or model switching fees
Funding – $53.5M raised ($25M Series A July 2024, FPV/Race Capital)
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
Limitations & Considerations
Developer-First Platform – Optimized for teams with coding skills, NOT business users
NO Visual Agent Builder – Agent creation requires Python SDK, not for non-technical users
NO Native Messaging/Widget – NO Slack, WhatsApp, Teams, embeddable chat needs custom development
HIPAA Gap – No explicit certification, healthcare needs sales verification
NOT Ideal For – SMBs without dev resources, teams needing visual builders/messaging
⚠️ 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
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
Chat API – Multi-turn dialog with state/memory of previous turns for context
Retrieval-Augmented Generation (RAG) – Document mode specifies which documents to reference
Generative AI Extraction – Automatically extracts answers from responses for reuse
Intent-Based AI – Beyond keyword search, surfaces relevant snippets for plain English
Vector + LLM search – Smart retrieval with generative answers, context-aware responses
Mockingbird LLM – Proprietary model with source citations (details )
Multi-turn conversations – Conversation history tracking for smooth back-and-forth dialogue
✅ #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 & Flexibility ( Behavior & Knowledge) N/A
Indexing control – Configure chunk sizes, metadata tags, retrieval parameters
Search weighting – Tune semantic vs lexical search balance per query
Domain tuning – Adjust prompt templates and relevance thresholds for specialty domains
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
Additional Considerations N/A
✅ Factual scoring – Hybrid search with reranking provides unique factual-consistency scores
Flexible deployment – Public cloud, VPC, or on-prem for varied compliance needs
Active development – Regular feature releases and integrations keep platform current
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
N/A
✅ 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 private
Private deployments – VPC or on-premise for data sovereignty and network isolation
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
N/A
Enterprise support – Dedicated channels and SLA-backed help for enterprise customers
Microsoft network – Extensive infrastructure, forums, technical guides backed by Microsoft
Comprehensive docs – API references, integration guides, SDKs at docs.vectara.com
Sample code – Pre-built examples, Jupyter notebooks, quick-start guides for rapid integration
Active community – Developer forums for peer support, knowledge sharing, best practices
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
Join the Discussion
Loading comments...