United States verdict (TL;DR)
Verified 2026-05-17LangSmith and LangGraph are the developer-standard pair for production agentic workflows in the US: LangSmith for observability and evals, LangGraph for orchestration. Salesforce Agentforce owns the Salesforce-customer install base; Microsoft Copilot Studio owns M365. ServiceNow AI Agents (Now Assist) is the default for ITSM and enterprise workflow automation at ServiceNow shops. CrewAI is the open-source multi-agent standard. n8n is engineering-led workflow automation with AI nodes. The 2026 regulatory overlay: Colorado AI Act (effective 2026-02-01) requires impact assessments for high-risk AI systems; NYC bias-audit legislation has spillover beyond hiring into autonomous customer-facing agents; NIST AI RMF voluntary framework shapes US enterprise AI governance posture.
Picks for United States
- Developer-first agent observability and evals: langsmith The US engineering community standard for agent tracing, evaluation, and prompt management. Default alongside LangGraph for any team shipping agents to production.
- US Salesforce-anchored enterprise extending CRM with agents: agentforce Native Salesforce agent platform. Default for US enterprises on Salesforce Sales Cloud, Service Cloud, and Marketing Cloud. No vendor procurement hurdle; already contracted.
- US Microsoft 365 and Azure enterprise: copilot-studio Native Power Platform agent builder. Default for US enterprises on M365 E3/E5 where Copilot Studio is bundled or discounted. Azure OpenAI integration native.
- US enterprise ITSM and workflow automation at ServiceNow shops: servicenow-ai-agents Now Assist GA in 2025 brought agentic automation to ServiceNow ITSM, HR Service Delivery, and CSM. Default for US Fortune 500 running ServiceNow.
- Engineering teams self-hosting agent orchestration: langgraph Open-source, self-hostable agent orchestration from LangChain. Preferred by US platform engineering teams building custom multi-step agent workflows without vendor lock-in.
- Open-source multi-agent framework for US engineering teams: crewai CrewAI is the standard open-source multi-agent orchestration framework in US developer communities. Strong GitHub adoption, thriving r/CrewAI community. Best when you need defined roles and crew-level coordination.
- US SMB no-code agent automation: lindy Best no-code AI agent builder for US SMB ops automation. Non-engineers at 10-200 employee companies can build scheduling, inbox, and lead-routing agents without SDKs.
How the ai agent platforms market looks in United States
The US is the deepest and most competitive AI agent platform market globally, home to every major developer SDK, the largest no-code agent platform vendors, and the enterprise giants (Salesforce, Microsoft, ServiceNow) shipping agents on top of existing CRM and ITSM install bases. Buyers face three genuinely different procurement journeys.
The developer journey runs through LangChain's ecosystem. LangGraph handles orchestration; LangSmith handles observability, evaluation, and prompt management. At US Series A-D product companies and enterprise engineering teams (Replit, Notion, and AWS internal teams have publicly referenced LangGraph use), this pair is the standard. AWS Bedrock Agents and Vertex AI Agent Builder are cloud-bundled alternatives that undercut LangSmith/LangGraph on simplicity but offer less orchestration depth. OpenAI Assistants API is the third developer path, simpler but less observable.
The enterprise bundling journey is dominated by three acquisitions and platform extensions: Agentforce (Salesforce), Copilot Studio (Microsoft), and ServiceNow AI Agents. All three follow the same pattern: the buyer already has a six-to-eight-figure contract with the parent platform; agents are sold as an add-on or included tier. The switching cost calculus is different, this is not a competitive procurement, it's an extension decision.
The no-code and low-code journey runs through Lindy (best SMB), Relevance AI (best mid-market), Make and n8n (best for workflow-first users). n8n's self-hosted version is widely used by US engineering teams that want workflow automation without vendor lock-in. Make (Integromat, Czech-built) remains the most widely used no-code workflow automation tool by seat count in the US mid-market.
The 2026 regulatory context is emerging but not yet binding. Colorado AI Act (effective 2026-02-01) requires impact assessments for high-risk AI; NIST AI RMF is the voluntary governance standard most US enterprise AI procurement teams reference; no federal AI agent-specific statute exists as of Q2 2026. State-level AI laws are the relevant procurement checkpoint.
NIST AI RMF (voluntary) is the US enterprise governance standard; most large US enterprise buyers now include NIST AI RMF alignment questions in AI vendor procurement questionnaires. Colorado AI Act (effective 2026-02-01) requires impact assessments for high-risk AI deployed on Colorado consumers; California AB 2013 (effective 2026) requires training data transparency. NYC Local Law 144 applies to automated employment decision tools in hiring; spillover into customer-facing autonomous agents is emerging. SOC 2 Type II is table-stakes for US enterprise AI vendor contracts. HIPAA considerations apply when agents handle PHI (LangSmith Enterprise and ServiceNow offer BAA; Agentforce Enterprise offers HIPAA BAA; Copilot Studio with Azure Health Data Services). FedRAMP: only ServiceNow (FedRAMP High authorized) and Microsoft Copilot Studio (via Azure FedRAMP) have viable US federal deployment paths.
Quick comparison, ranked for United States
| Product | Best for | Starts at | 10-emp/mo* | Pricing | G2 | Geo |
|---|---|---|---|---|---|---|
| 1 LangSmith | Engineering teams building production agents | $0 + $0/emp | $0 | 4.5 | Global; strongest in US, EU, UK | |
| 6 Salesforce Agentforce | Salesforce-anchored enterprises | $2 | $2 | 4.4 | Global; strongest in US, EU, UK | |
| 7 Microsoft Copilot Studio | Microsoft-anchored enterprises | $0 + $0/emp | $0 | 4.3 | Global; strongest in US, EU, UK; worldwide | |
| 8 ServiceNow AI Agents | ServiceNow-anchored enterprises | Quote | - | 4.4 | Global; strongest in US, EU, UK | |
| 9 LangGraph | Engineering teams building production agents | $0 + $0/emp | $0 | 4.5 | Global | |
| 4 CrewAI | Engineering teams building multi-agent systems | $0 + $0/emp | $0 | 4.6 | Global | |
| 3 Relevance AI | Mid-market with mix of ops and engineering | $0 + $0/emp | $0 | 4.6 | Global; strongest in US, AU, UK | |
| 5 n8n | Engineering-led automation teams | $0 + $0/emp | $0 | 4.7 | Global; strongest in EU, US | |
| 2 Lindy | SMB ops teams | $0 + $0/emp | $0 | 4.7 | Global; strongest in US | |
| 10 Make (formerly Integromat) | Mid-market non-engineering teams | $0 + $0/emp | $0 | 4.7 | Global; strongest in EU, US |
*10-employee monthly cost = base fee + (per-employee × 10) using the lowest published tier. For opaque-pricing vendors, no value is shown.
What buyers in United States actually pay
Median annual deal size by employee band, in USD. Crowdsourced from anonymized buyer disclosures.
| Product | Employee band | Median annual (USD) | Sample | Notes |
|---|---|---|---|---|
| LangSmith | Solo / Developer (free tier) | $0 | 87 | 5K traces/month free |
| LangSmith | Small team / Plus | $1,872 | 56 | $39/seat/month |
| LangSmith | Enterprise | $24,000 | 28 | Custom; includes SSO and SLA |
| Salesforce Agentforce | Enterprise (per-conversation) | $120,000 | 34 | $2/conversation baseline; large enterprise volume contracts vary |
| Microsoft Copilot Studio | M365 E3/E5 bundle (1,000+ seats) | $0 | 67 | Included in M365 Copilot bundle; standalone $200/tenant + $0.01/message |
| n8n | Self-hosted (open-source) | $0 | 112 | Self-hosted free; Cloud Starter $240/year |
| Relevance AI | SMB (10-200 employees) | $4,788 | 41 | $399/month Business tier |
United States-built or United States-strong vendors worth knowing
Not yet ranked in our global top 10, but credible options for United States buyers and worth a shortlist.
AWS Bedrock Agents
Visit ↗AWS-native agent orchestration. Default for US enterprises running inference on Amazon Bedrock. No separate contract; billed as Bedrock usage. Weaker observability than LangSmith but zero new vendor procurement.
Vertex AI Agent Builder
Visit ↗Google Cloud-native agent builder. Default for US teams on Google Cloud running Gemini models. Best for US enterprises with existing GCP contracts.
Moveworks
Visit ↗Mountain View-based enterprise AI agent platform for employee service automation (IT, HR, Finance). Strong Fortune 500 US install base. Series D funded at $2.1B valuation. Not a general agent builder; enterprise-only.
Letta (formerly MemGPT)
Visit ↗San Francisco-based open-source agent memory and stateful agent framework. Spun out of UC Berkeley research. Strong US developer community following for agents needing persistent memory architectures.
All 10, ranked for United States
Same intelligence as the global ranking, vendor trust, review patterns, verified pricing, compliance, reordered for the United States market.
LangSmith
Industry-standard agent observability and evaluation platform.
LangSmith is the observability and evaluation platform from LangChain (the company behind LangChain and LangGraph), founded 2022, last valued $1.25B+ (2024). The product covers agent tracing, evaluation, prompt management, and debugging, purpose-built for production agent deployments. Strengths: native LangChain/LangGraph integration, deepest agent tracing in category, mature evaluation framework (LangSmith Evals), and fastest product velocity. Best fit for engineering teams shipping agents to production. Trade-offs: pricing scales with traces ($0-$199+/seat plus per-trace usage), framework-agnostic mode less polished than native LangChain integration, and competition from purpose-built challengers (Braintrust, Helicone) is intensifying.
Engineering teams (5-500 engineers) building production agents using LangChain/LangGraph or any framework, prioritizing observability and evaluation depth.
Non-engineering teams (Lindy/Relevance AI better fit), Salesforce-anchored enterprises (Agentforce native better), or buyers wanting fully managed agent platform without engineering effort.
Strengths
- Industry-standard agent observability
- Native LangChain/LangGraph integration
- Deepest agent tracing in category
- Mature LangSmith Evals framework
- Fastest product velocity
- Fits production agent deployments
Weaknesses
- Pricing scales with traces (per-usage costs)
- Framework-agnostic mode less polished
- Competition intensifying from Braintrust/Helicone
- Per-seat scaling adds up at higher tiers
- Some enterprise governance features still maturing
Pricing tiers
public- Developer5K traces/month free$0+$0 /mo +/emp
- PlusPer seat; 10K traces/seat$39 /mo
- EnterpriseCustom; SSO, SOC 2, dedicated supportQuote
- · Per-trace overage costs scale fast
- · Higher-volume orgs hit per-seat ceilings quickly
- · Custom evaluators consume LLM API budget
Key features
- +Agent tracing and debugging
- +LangSmith Evals (eval framework)
- +Prompt management and versioning
- +Production monitoring
- +Native LangChain/LangGraph integration
- +Framework-agnostic SDK
- +Annotation queues for human feedback
Salesforce Agentforce
Native Salesforce agent platform extending CRM with AI agents.
Salesforce Agentforce is Salesforce's native AI agent platform, launched 2024 (originally branded "Einstein Agentforce"). The product extends Salesforce CRM with AI agents for sales, service, marketing, and commerce. Strengths: native Salesforce data and metadata access (no data movement required), default for Salesforce-anchored enterprises, Atlas Reasoning Engine for agent planning, and aggressive roadmap. Trade-offs: outside Salesforce ecosystem the product is irrelevant, pricing meaningful (per-conversation $2 + per-Agentforce-seat tiers), and many capabilities still maturing as of 2026.
Salesforce-anchored enterprises (1,000-50,000 employees) extending CRM with AI agents, particularly customer service, sales, and marketing agents on Salesforce data.
Non-Salesforce shops (LangSmith/CrewAI/Lindy better), engineering-led agent building (LangSmith/CrewAI better), or value-driven mid-market.
Strengths
- Native Salesforce data access
- Default for Salesforce-anchored enterprises
- Atlas Reasoning Engine
- Strong customer service agent use case
- Public company financial transparency
- Massive Salesforce sales motion
Weaknesses
- Outside Salesforce ecosystem irrelevant
- Pricing meaningful (per-conversation $2 + seats)
- Many capabilities still maturing
- Implementation heavy for non-trivial agents
- Support depends on tier
Pricing tiers
public- AgentforcePer conversation; consumption-based$2 /mo
- Agentforce Studio (build)Per seat; agent builder accessQuote
- Enterprise BundleCustom; bundled with Salesforce Sales/Service CloudQuote
- · Per-conversation costs scale with usage
- · Salesforce platform license required
- · Implementation services
Key features
- +Native Salesforce data integration
- +Agentforce Studio (low-code agent builder)
- +Atlas Reasoning Engine
- +Pre-built agent templates (sales, service, etc.)
- +Salesforce Data Cloud integration
- +Voice + chat channels
- +Mobile apps
Microsoft Copilot Studio
Native Microsoft 365 / Power Platform agent builder.
Microsoft Copilot Studio is Microsoft's low-code agent builder, founded 2023 (rebranded from Power Virtual Agents). The product covers building AI agents for Microsoft 365, Teams, and Power Platform integration. Strengths: bundled-or-near-bundled with Microsoft 365 enterprise contracts, native Microsoft Graph integration (Teams, SharePoint, Outlook), and strong fit for Microsoft-anchored enterprises. Trade-offs: outside Microsoft ecosystem the product is meaningfully weaker, agent capability ceiling lower than dev SDKs (Copilot Studio is great for predictable Microsoft workflows; less great for novel multi-step tasks), and pricing creates surprise costs (per-message billing).
Microsoft 365 enterprise customers (1,000+ employees) extending Microsoft 365 with low-code agents, particularly Teams, Outlook, and SharePoint workflows.
Non-Microsoft shops (LangSmith/Lindy better), engineering-led agent building (LangSmith/CrewAI better), or buyers needing deep multi-agent orchestration.
Strengths
- Bundled or near-bundled with Microsoft 365 enterprise
- Native Microsoft Graph integration
- Fits Microsoft-anchored enterprises
- Power Platform integration
- Public company financial transparency
- FedRAMP High authorized
Weaknesses
- Outside Microsoft ecosystem meaningfully weaker
- Agent capability ceiling lower than dev SDKs
- Per-message pricing creates surprise costs
- Customer support varies by region
- Innovation pace below Salesforce Agentforce
Pricing tiers
public- Pay-as-you-goPer-message billing; ~$0.01/message$0+$0 /mo +/emp
- Copilot Studio ProPer tenant; 25K messages/month$200 /mo
- M365 BundledBundled with M365 E5 (some features)Quote
- · Per-message costs scale with usage
- · Premium features in higher tiers
- · M365 license required
Key features
- +Low-code agent builder
- +Native Microsoft Graph integration
- +Power Platform integration
- +Teams + Outlook + SharePoint workflows
- +Voice + chat channels
- +Pre-built templates
- +Mobile apps
ServiceNow AI Agents
Native ServiceNow agent platform for enterprise ITSM workflows.
ServiceNow AI Agents (part of the Now Assist family) is ServiceNow's native AI agent platform. The product extends ServiceNow ITSM, ITOM, HRSD, and CSM with AI agents for incident routing, ticket triage, and workflow automation. Strengths: native ServiceNow data and workflow access, default for ServiceNow-anchored enterprises (10,000+ employees), and tight integration with the ServiceNow data graph. Trade-offs: outside ServiceNow ecosystem the product is irrelevant, pricing meaningful (Now Assist licenses run $20K-$1M+/year), and capability still catching up to Salesforce Agentforce in non-ITSM use cases.
ServiceNow-anchored enterprises (5,000-100,000 employees) extending ITSM, ITOM, HRSD with AI agents, particularly incident routing, ticket triage, and approval workflows.
Non-ServiceNow shops (LangSmith/CrewAI better), customer-facing AI agents (Salesforce Agentforce better), or mid-market wanting lower TCO (overpriced).
Strengths
- Native ServiceNow data integration
- Default for ServiceNow-anchored enterprises
- Strong ITSM agent use case (incident, ticket triage)
- Tight ServiceNow data graph access
- Public company financial transparency
- Mature enterprise compliance
Weaknesses
- Outside ServiceNow ecosystem irrelevant
- Pricing meaningful (Now Assist $20K-$1M+/year)
- Capability catching up to Agentforce in non-ITSM
- Implementation heavy
- Support inconsistency reported
Pricing tiers
opaque- Now Assist (Pro Plus)~$20K-$200K/year typicalQuote
- Now Assist (Enterprise)$200K-$1M+/year for large enterprisesQuote
- · Bundled with ServiceNow platform license
- · Per-employee scaling
- · Implementation services
Key features
- +Native ServiceNow data integration
- +AI Agent Studio
- +Pre-built ITSM, ITOM, HRSD agents
- +Now LLM (proprietary)
- +Multi-channel (email, Teams, Slack)
- +Mobile apps
LangGraph
Open-source agent orchestration framework from LangChain.
LangGraph is the agent orchestration framework from LangChain, launched 2024. The product is a graph-based framework for building stateful, multi-actor agents, designed for production-grade agent systems where reliability and observability matter. Strengths: graph-based stateful agent architecture, native LangSmith integration, LangGraph Cloud for managed deployment, and strong fit for production agent systems. Best fit for engineering teams building production agents with non-trivial state and control flow. Trade-offs: framework-only requires engineering effort, learning curve steeper than CrewAI, and observability requires LangSmith (not bundled).
Engineering teams (5-200 engineers) building production agent systems with non-trivial state, control flow, and observability requirements.
Non-engineering teams (Lindy/Relevance AI better fit), pure single-agent use cases (LangChain or OpenAI Agents simpler), or buyers wanting fully managed without engineering.
Strengths
- Graph-based stateful agent architecture
- Native LangSmith integration
- LangGraph Cloud for managed deployment
- Built for production agent systems
- Open-source (MIT)
- Time-travel debugging
Weaknesses
- Framework-only requires engineering effort
- Learning curve steeper than CrewAI
- Observability requires LangSmith
- Documentation gaps in advanced features
- Less mature than LangChain
Pricing tiers
public- Open SourceSelf-hosted; bring your own LLM$0+$0 /mo +/emp
- LangGraph CloudManaged deployment; bundled with LangSmithQuote
- EnterpriseCustom; SSO + governanceQuote
- · LLM API costs separate
- · LangSmith for observability
- · LangGraph Cloud usage scales
Key features
- +Graph-based agent orchestration
- +Stateful multi-actor agents
- +Native LangSmith integration
- +LangGraph Cloud (managed deployment)
- +Time-travel debugging
- +Human-in-the-loop primitives
- +Streaming + interruption support
CrewAI
Open-source multi-agent orchestration framework.
CrewAI is the open-source multi-agent orchestration framework, founded 2023 by João Moura. The product is a Python framework for building agent crews, multiple agents that collaborate on complex tasks with role-based responsibilities. Strengths: clean role-based agent abstractions (researcher, writer, reviewer), open-source with active community, strong fit for engineering teams building multi-agent systems, and CrewAI Plus for managed deployment. Trade-offs: framework-only approach requires engineering effort, Python-only, and observability requires LangSmith or similar (not bundled).
Engineering teams (5-100 engineers) building multi-agent systems with role-based responsibilities, comfortable with Python framework adoption.
Non-engineering teams (Lindy/Relevance AI better fit), single-agent use cases (LangChain/LangGraph more flexible), or non-Python shops.
Strengths
- Open-source (Apache 2.0)
- Clean role-based agent abstractions
- Made for multi-agent systems
- Active community
- CrewAI Plus for managed deployment
- Founder-led; strong product velocity
Weaknesses
- Framework-only requires engineering effort
- Python-only
- Observability requires separate tool (LangSmith)
- Documentation gaps in advanced features
- Smaller community than LangChain
Pricing tiers
public- Open SourceSelf-hosted; bring your own LLM$0+$0 /mo +/emp
- CrewAI PlusPer workspace; managed deployment$99 /mo
- EnterpriseCustom; SSO + governanceQuote
- · LLM API costs separate
- · Production deployment infra costs
Key features
- +Multi-agent orchestration
- +Role-based agent abstractions
- +Tool use
- +Agent collaboration patterns
- +Open-source framework
- +CrewAI Studio for visual building
- +CrewAI Plus for managed deployment
Relevance AI
Mid-market low-code agent platform with strong pre-built skills.
Relevance AI is the mid-market low-code AI agent platform, founded 2020. The product covers agent building, deployment, and management with a low-code interface that engineering teams and ops teams both use. Strengths: strong pre-built skills library, mid-market sweet spot ($199-$1,499/month), and tight CRM integrations. Best fit for mid-market companies (50-500 employees) wanting low-code agents with engineering escape hatches. Trade-offs: not the right fit for pure no-code SMB use (Lindy better) or pure dev-SDK engineering (LangSmith + framework better), and product velocity has been mixed in 2024-2025.
Mid-market companies (50-500 employees) wanting low-code agent platform with engineering escape hatches and strong CRM integrations.
Pure no-code SMBs (Lindy better fit), pure engineering teams (LangSmith + framework better), or enterprise needing deep governance (Agentforce/ServiceNow better).
Strengths
- Strong pre-built skills library
- Mid-market sweet spot ($199-$1,499/month)
- Low-code with engineering escape hatches
- Tight CRM integrations (Salesforce, HubSpot)
- Multi-agent orchestration
- Founder-led
Weaknesses
- Not the right fit for pure no-code SMB
- Product velocity mixed 2024-2025
- Support is hit-or-miss
- Smaller community than LangSmith
- Some integration gaps vs Lindy
Pricing tiers
public- Free100 credits/month$0+$0 /mo +/emp
- Pro10K credits/month$199 /mo
- Team50K credits/month$599 /mo
- Business200K credits/month$1499 /mo
- EnterpriseCustom; SSO + governanceQuote
- · Credit overage costs
- · Some advanced integrations gated
- · Per-seat pricing at higher tiers
Key features
- +Low-code agent builder
- +Multi-agent orchestration
- +Pre-built skills library
- +Custom skills (Python/JavaScript)
- +CRM integrations native
- +Workflow triggers
- +Agent monitoring
n8n
Open-source workflow automation with AI nodes, self-hostable.
n8n is the open-source workflow automation platform with AI nodes, founded 2019 in Berlin. The product is a fair-code-licensed automation tool (similar to Zapier/Make but self-hostable) that added agent capabilities through AI nodes 2024-2025. Strengths: self-hostable open-source (huge for regulated industries), 400+ integrations, AI agent nodes for adding LLMs into workflows, and engineering-friendly. Best fit for engineering-led automation teams wanting self-hosted control. Trade-offs: not a pure agent platform (it's workflow automation with AI added), no-code experience less polished than Lindy, and SaaS pricing at scale comparable to commercial alternatives.
Engineering-led automation teams (10-1,000 employees) wanting self-hosted control, large integration footprint, and AI nodes within workflow automation.
Pure no-code SMBs (Lindy better fit), pure agent engineering (CrewAI/LangGraph better), or buyers wanting fully managed without DevOps.
Strengths
- Self-hostable open-source (fair-code license)
- 400+ integrations
- AI agent nodes for LLM workflows
- Engineering-friendly (custom nodes)
- Right call for regulated industries
- Active community
Weaknesses
- Not a pure agent platform (workflow + AI)
- No-code UX less polished than Lindy
- SaaS pricing at scale comparable to commercial
- Documentation gaps for AI features
- Customer support on community tier only
Pricing tiers
public- Self-hosted CommunityOpen-source; unlimited$0+$0 /mo +/emp
- Cloud Starter5K executions/month$24 /mo
- Cloud Pro10K executions/month$60 /mo
- EnterpriseCustom; self-hosted + SSOQuote
- · Self-hosted infra costs
- · Per-execution overage on Cloud
- · AI LLM API costs separate
Key features
- +Workflow automation
- +AI agent nodes
- +400+ integrations
- +Custom nodes (JavaScript)
- +Self-hostable open-source
- +Cloud SaaS option
- +Fair-code license
Lindy
No-code AI agent builder for SMB ops automation.
Lindy is the no-code AI agent platform for SMB ops automation, founded 2022 by Flo Crivello. The product lets non-engineers build agents that handle scheduling, inbox management, lead routing, and recurring ops tasks. Strengths: no-code agent building (no SDKs required), strong fit for SMB ops automation, modern UX, and aggressive product velocity. Best fit for SMBs (10-200 employees) wanting agent-driven workflow automation without engineering effort. Trade-offs: agent capability ceiling lower than dev SDKs (Lindy is great for predictable workflows; less great for novel multi-step tasks), pricing per-task can scale unpredictably, and enterprise governance still maturing.
SMB ops teams (10-200 employees) wanting no-code agent automation for predictable workflows (scheduling, inbox, lead routing, recurring tasks).
Engineering teams building novel agents (LangSmith + dev SDKs better), enterprise needing deep governance (Salesforce/ServiceNow agents better), or pure observability use case.
Strengths
- No-code agent builder (no SDKs required)
- Works for SMB ops automation
- Modern UX
- Aggressive product velocity
- Pre-built skills for common workflows
- Founder-led; strong VC backing
Weaknesses
- Agent capability ceiling lower than dev SDKs
- Pricing per-task scales unpredictably
- Enterprise governance still maturing
- Support response times vary
- Less suitable for novel multi-step tasks
Pricing tiers
public- Free400 tasks/month$0+$0 /mo +/emp
- Pro5,000 tasks/month$49 /mo
- Business30,000 tasks/month$199 /mo
- EnterpriseCustom; SSO + governanceQuote
- · Per-task overage costs
- · Some advanced integrations gated to higher tiers
- · Per-seat pricing on Business+
Key features
- +No-code agent builder
- +Pre-built skills (scheduling, email, lead routing)
- +Calendar integration
- +Email integration (Gmail, Outlook)
- +CRM integration (Salesforce, HubSpot)
- +Agent triggers (scheduled, event-based)
- +Mobile apps
Make (formerly Integromat)
Mid-market no-code workflow automation with AI agent nodes.
Make (formerly Integromat) is the mid-market no-code workflow automation platform, founded 2012, acquired by Celonis in 2020 and rebranded to Make in 2022. The product is similar to Zapier but with more visual flexibility and better mid-market pricing, and added AI agent capabilities through OpenAI/Anthropic nodes 2023-2024. Strengths: visual scenario builder, 1,500+ integrations, AI nodes for adding LLMs into workflows, and competitive pricing. Best fit for mid-market non-engineering teams extending existing automation. Trade-offs: not a pure agent platform, AI capability ceiling lower than dedicated agent tools, and post-Celonis direction has been measured.
Mid-market non-engineering teams (50-1,000 employees) extending existing workflow automation with AI nodes, primarily Zapier alternatives at higher complexity.
Pure agent platform needs (LangSmith/CrewAI/Lindy better), engineering-led automation (n8n better), or buyers wanting deepest AI integration.
Strengths
- Visual scenario builder
- 1,500+ integrations
- AI nodes (OpenAI, Anthropic)
- Competitive mid-market pricing
- Established 12+ year track record
- Best for non-engineers
Weaknesses
- Not a pure agent platform
- AI capability ceiling lower than dedicated tools
- Post-Celonis product velocity measured
- Some complexity in advanced scenarios
- Support response times vary
Pricing tiers
public- Free1,000 ops/month$0+$0 /mo +/emp
- Core10K ops/month$9 /mo
- Pro10K ops/month + advanced$16 /mo
- TeamsPer user; multi-user$29 /mo
- EnterpriseCustom; advanced featuresQuote
- · Per-operation overage costs
- · AI node usage scales with LLM API costs
- · Some advanced features gated
Key features
- +Visual scenario builder
- +1,500+ integrations
- +AI nodes (OpenAI, Anthropic, etc.)
- +Custom apps (developer SDK)
- +Webhooks and APIs
- +Mobile apps
- +Schedule and event-based triggers
Frequently asked questions
The questions buyers actually ask before they sign.
LangGraph vs CrewAI vs Agentforce: which for US enterprise agentic workflows?
Does Colorado AI Act or any US law require AI agent disclosures?
Which AI agent platforms have FedRAMP authorization for US federal buyers?
LangSmith vs CrewAI vs Lindy, which is right for me?
How does this differ from AI Coding Assistants?
How much should I budget for AI agent platforms?
Do I need observability for agents?
When should I use a dev SDK vs a no-code platform?
How does Salesforce Agentforce compare to LangChain?
Can I evaluate agent platforms via free trial?
How does this overlap with AI SDR and chatbots?
Final word
Looking at a different market? See the global AI Agent Platforms ranking, or pick another country at the top of this page.
Last updated 2026-05-17. Local pricing reverified quarterly. Found something inaccurate? Tell us.