Cohere vs Lindy.ai

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 Cohere and Lindy.ai 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 Cohere and Lindy.ai, 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 Cohere if: you value industry-leading deployment flexibility: saas, vpc (<1 day), air-gapped on-premise with zero cohere infrastructure access - unmatched among major ai providers
  • Choose Lindy.ai if: you value exceptional no-code usability: 4.9/5 g2 rating, 30-second setup vs 15-60 min with zapier/make

About Cohere

Cohere Landing Page Screenshot

Cohere is enterprise rag api platform with unmatched deployment flexibility. Enterprise-first RAG API platform founded 2019 by Transformer co-author Aidan Gomez with $1.54B raised at $7B valuation. Offers Command A (256K context), Embed v4.0 (multimodal), Rerank 3.5 (128K), and 100+ connectors via Compass. Unmatched deployment flexibility: SaaS, VPC, air-gapped on-premise with zero Cohere data access. SOC 2/ISO 27001/ISO 42001 certified. NO native chat widgets, Slack/WhatsApp integrations, or visual builders—API-first for developers building custom solutions. Token-based pricing from free trials to enterprise. Founded in 2019, headquartered in Toronto, Canada / San Francisco, CA, USA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
89/100
Starting Price
Custom

About Lindy.ai

Lindy.ai Landing Page Screenshot

Lindy.ai is ai-powered personal assistant for workflow automation. No-code AI agent platform positioning as 'AI employees' for workflow automation, NOT developer-focused RAG platform. 5,000+ integrations via Pipedream, Claude Sonnet 4.5 default, $5.1M revenue (Oct 2024), 4.9/5 G2 rating. Critical limitation: No public API or SDKs available. Founded in 2023, headquartered in San Francisco, CA, USA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
81/100
Starting Price
Custom

Key Differences at a Glance

In terms of user ratings, Cohere in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: RAG Platform versus AI Assistant. 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 cohere
Cohere
logo of lindy
Lindy.ai
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CustomGPTRECOMMENDED
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 Formats – PDF, DOCX, XLSX, CSV, TXT, HTML (20MB per file)
  • Cloud Integrations – Drive, OneDrive, Dropbox, Notion, SharePoint, auto 24-hour sync
  • ⚠️ Storage Limits – 1M chars (Free), 20M (Pro), 50M (Business)
  • ⚠️ Search Constraint – Fuzziness <100 limits to first 1,500 files
  • 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
  • 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
  • 5,000+ Apps – Via Pipedream Connect with 2,500+ ready actions
  • Messaging – Slack, WhatsApp, Teams, Telegram, Discord, Twilio SMS
  • CRM – Salesforce (24 actions), HubSpot, Pipedrive, Zoho CRM
  • Productivity – Notion, Airtable, Google Workspace (Gmail, Calendar, Docs, Sheets, Drive)
  • Webhooks + HTTP – Inbound triggers and outbound API calls
  • 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
Core Agent Features
  • 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
  • Agent Autonomy Focus – Task execution vs conversational chatbot
  • Multi-Lingual – 30+ (voice), 50+ (transcription), 85+ (text)
  • ✅ Lead Capture – Real-time qualification, CRM sync (70% higher conversion claimed)
  • Agent Evals – Benchmarking with regression prevention
  • 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
Customization & Branding
  • 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
  • Widget – Custom name, accent color, logo for expanded/collapsed states
  • Domain Restrictions – Control allowed deployment domains
  • Memory Snippets – Learning preferences saved across sessions
  • ⚠️ White-Label Unclear – Complete branding removal not explicitly confirmed
  • 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
L L M Model Options
  • 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
  • Anthropic Claude – Sonnet 4.5 (default), Sonnet 3.7, Haiku 3.5
  • OpenAI – GPT-5, GPT-5 Codex, GPT-4o, GPT-4 Turbo, o3, o1
  • Google Gemini – 2.5 Pro, 2.5 Flash, 2.0 Flash
  • Per-Action Selection – Manual model choice affects credit consumption
  • ⚠️ No Auto-Routing – No dynamic model switching
  • 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
  • ⚠️ CRITICAL LIMITATION – NO public REST API, GraphQL, or SDKs
  • Workarounds Only – Inbound webhooks, HTTP actions, Code sandboxes (~150ms)
  • User-Focused Docs – Lindy Academy for business users, NO API reference
  • 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
Performance & Accuracy
  • 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
  • Hybrid Search – Semantic + keyword with Fuzziness slider (0-100)
  • Hallucination Reduction – Human confirmation before actions
  • ⚠️ NO Published Benchmarks – No RAG accuracy or latency metrics
  • ⚠️ Black Box – Vector database and embedding models undisclosed
  • 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
Pricing & Scalability
  • 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
  • Free: $0 – 400 credits, 1M char knowledge base
  • Pro: $49.99 – 5,000 credits, 20M chars, phone calls, Lindy branding
  • Business: $199.99-$299.99 – 20K-30K credits, 50M chars, custom branding
  • Enterprise: Custom – SSO, SCIM, dedicated support, custom training
  • ⚠️ Unpredictable Costs – Credit depletion speed is primary user complaint
  • 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
Security & Privacy
  • 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
  • SOC 2 Type II, HIPAA, GDPR, PIPEDA, CCPA – Comprehensive compliance
  • Encryption – AES-256 at rest, TLS 1.2+ in transit
  • Enterprise SSO + SCIM – Automated user lifecycle management
  • ⚠️ US Data Residency Only – No explicit EU option documented
  • 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
  • Workflow Performance – Agent action visibility with recent runs
  • Audit Logs – User actions, data access on Business/Enterprise plans
  • ⚠️ Log Retention – 1 day (Free) severely constrains troubleshooting
  • ⚠️ NO RAG Metrics – Cannot track retrieval precision or recall
  • 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
Support & Ecosystem
  • 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
  • Email Support – support@lindy.ai, security@lindy.ai, privacy@lindy.ai
  • Slack + Forum – community.lindy.ai for peer support
  • 100+ Templates – Pre-built workflow automation scenarios
  • ⚠️ Support Inconsistency – Mixed reviews on responsiveness for lower tiers
  • 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
  • ✅ 4.9/5 G2 Rating – 109+ reviews validate ease of use
  • Agent Builder – Natural language prompts create complex agents
  • Setup Speed – 30 seconds vs 15-60 minutes with Zapier/Make
  • Drag-Drop Builder – Visual workflow construction, zero coding
  • 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
Multi- Lingual Support
  • 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
  • ⚠️ NOT a RAG Platform – Workflow automation for business users vs developers
  • Black-Box RAG – Hybrid search with no exposed retrieval controls
  • NO API, SDKs, CLI – No programmatic access for developers
  • 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
Competitive Positioning
  • 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)
  • ✅ Primary Advantage – 4.9/5 G2 usability with 5,000+ integrations
  • Financial Validation – $5.1M revenue, $50M+ funding (Menlo, Battery, Coatue)
  • Claude Sonnet 4.5 Default – Drove 10x customer growth
  • ⚠️ Pricing Unpredictability – Credit-based model most common complaint
  • 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
A I Models
  • 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
  • Default: Claude Sonnet 4.5 – 'Almost no one overrides' per Anthropic
  • Claude Family – Sonnet 4.5, 3.7, Haiku 3.5 (200K context)
  • OpenAI – GPT-5, GPT-4o, GPT-4 Turbo, o3, o1
  • Google – Gemini 2.5 Pro, 2.5 Flash, 2.0 Flash
  • 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
  • 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 + keyword with Fuzziness slider (0-100)
  • Document Processing – PDF, DOCX, XLSX, CSV, TXT, HTML (20MB)
  • Cloud Integration – Auto 24-hour sync (Drive, OneDrive, Dropbox, Notion, SharePoint)
  • ⚠️ Black Box – Vector database, embedding models undisclosed
  • ⚠️ NO Developer Control – Cannot customize retrieval parameters
  • 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
  • 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)
  • Sales Automation – Lead qualification, scoring, enrichment, CRM syncing
  • Customer Support – Email triage, routing, FAQ, escalation
  • Voice Agents (Gaia) – 30+ language phone automation with call transfer
  • ⚠️ NOT Ideal For – Developers needing RAG APIs, EU residency
  • 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
Pricing & Plans
  • 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
  • Free: $0 – 400 credits, 1M chars, 1-day logs
  • Pro: $49.99 – 5K credits, 20M chars, phone calls
  • Business: $199.99-$299.99 – 20K-30K credits, 50M chars, branding
  • ⚠️ PRIMARY COMPLAINT – Unpredictable credit consumption difficult to budget
  • 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
  • NO Public REST API – Cannot manage agents programmatically
  • Black Box RAG – Vector database, embeddings undisclosed
  • Search Constraint – Fuzziness <100 limits to 1,500 files
  • Credit Unpredictability – Most common user complaint about costs
  • ⚠️ Platform Mismatch – Workflow automation vs RAG comparison misleading
  • 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
  • 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
N/A
  • ✅ #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
Autopilot & Computer Use ( Core Differentiator)
N/A
  • Unique Capability – AI agents operate cloud-based virtual computers
  • No API Required – Interact with any website/application through computer vision
  • E2B Sandboxes – Secure Python/JavaScript execution (~150ms startup)
  • ✅ Market Differentiation – Computer Use unique among no-code automation platforms
N/A
Multi- Agent Collaboration
N/A
  • Societies of Lindies – Multiple specialized agents with delegation rules
  • Context Preservation – Full conversation history passed between agents
  • Use Cases – Sales (SDR → AE → CS), Support (Triage → Technical → Escalation)
  • Learning Shared – Feedback across agent society for collective improvement
N/A
Lead Capture & Conversion
N/A
  • Real-Time Qualification – AI evaluates lead quality during conversation
  • Enrichment – Firmographic data, UTM attribution, validation
  • Auto CRM Sync – Qualified leads flow to Salesforce, HubSpot, Pipedrive, Zoho
  • ✅ 70% Higher Conversion – Claimed vs traditional forms (vendor claim)
N/A
Security & Compliance
N/A
  • SOC 2 Type II + HIPAA with BAA – Independently audited
  • GDPR + PIPEDA + CCPA – Multi-region privacy compliance
  • AES-256 + TLS 1.2+ – Encryption at rest and in transit
  • ⚠️ NO ISO 27001 – May limit enterprise procurement
  • 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
Support & Documentation
N/A
  • Lindy Academy – Step-by-step tutorials for business users
  • 100+ Templates – Pre-built workflows for common scenarios
  • Slack + Forum – community.lindy.ai for peer support
  • ⚠️ NO Developer Docs – No API reference or technical architecture
  • 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
Customization & Flexibility ( Behavior & Knowledge)
N/A
N/A
  • 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
N/A
  • 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

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Final Thoughts

Final Verdict: Cohere vs Lindy.ai

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

When to Choose Cohere

  • You value industry-leading deployment flexibility: saas, vpc (<1 day), air-gapped on-premise with zero cohere infrastructure access - unmatched among major ai providers
  • Enterprise security gold standard: SOC 2 Type II + ISO 27001 + ISO 42001 (AI Management System - rare) + GDPR + CCPA + UK Cyber Essentials
  • Grounded generation with inline citations showing exact document spans - built-in hallucination reduction vs competitors requiring custom implementation

Best For: Industry-leading deployment flexibility: SaaS, VPC (<1 day), air-gapped on-premise with ZERO Cohere infrastructure access - unmatched among major AI providers

When to Choose Lindy.ai

  • You value exceptional no-code usability: 4.9/5 g2 rating, 30-second setup vs 15-60 min with zapier/make
  • Massive integration ecosystem: 5,000+ apps via Pipedream Connect with 2,500+ pre-built actions
  • Claude Sonnet 4.5 default drives 10x customer growth - best-in-class language understanding

Best For: Exceptional no-code usability: 4.9/5 G2 rating, 30-second setup vs 15-60 min with Zapier/Make

Migration & Switching Considerations

Switching between Cohere and Lindy.ai 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

Cohere starts at custom pricing, while Lindy.ai 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 Cohere and Lindy.ai 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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