Best No-Code AI Agents

Buyer's guide · Updated quarterly

The best no-code AI agent builders for company work in 2026

An analysis of seven platforms for building AI agents without code, judged on the controls a company needs before an agent changes a real order, invoice or customer record.

An accounts manager initials a printed approval form at his desk while a colleague with a headset around her neck waits beside him holding a folder, trucks visible through the window.
The approval that matters is the one a person signs before the action, not after.
Contents
  1. The decision companies face
  2. How we evaluated the platforms
  3. The seven platforms, ranked
  4. The platforms compared
  5. Where agents have delivered results
  6. What agents cost
  7. The path to a first agent in production
  8. Questions buyers ask
  9. Sources

In brief

The best no-code AI agent builder depends on where the company’s records live and how much an agent may do alone. For agents that act inside the company’s own records with approval limits and a full log, OpenLazarus is our top pick. For Microsoft 365 companies, Copilot Studio has the deepest governance; for sales teams building many agents, Relevance AI has the most granular approvals; for an assistant across email, calendar and phone, Lindy.

  • Agents on your own records: OpenLazarus. AI teammates with an inbox and phone number work on the same records as staff, with limits per teammate and every action logged.
  • Microsoft 365 companies: Microsoft Copilot Studio. Agents governed by Purview audit logs, data policies and regional residency.
  • Sales and go-to-market agents: Relevance AI. An approval mode on every connection between an agent and a tool.
  • An assistant across inbox and phone: Lindy. Outside-impact actions wait for approval by default, across 1,500+ integrations.
  • Self-hosted agent workflows: n8n. Human review of any tool call, on servers the company runs.

The decision companies face

Most companies now use AI somewhere; far fewer let it act. In McKinsey's 2025 State of AI survey, 88% of organisations used AI in at least one function, 62% were at least experimenting with agents and 23% were scaling agents, usually in only one or two functions⁠1. Only 39% reported any effect on enterprise-wide earnings, most of it under 5%⁠1.

The gap between experiment and production is wide and expensive. Gartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027, citing escalating costs and unclear business value, and estimates that only about 130 of the thousands of vendors selling "agentic AI" offer real agents⁠2. Agents also still fail often. Stanford's 2026 AI Index reports that agents reached about 66% task success on OSWorld, a benchmark of real computer tasks, and still fail roughly one attempt in three on structured benchmarks⁠3.

That failure rate is why control matters more than capability. An agent that can change an order, issue a credit or email a customer will sometimes be wrong. OWASP names "excessive agency" among the top risks for AI applications (excessive functionality, permissions or autonomy) and recommends human approval for high-impact actions⁠4. IBM's 2025 breach study found that of the organisations reporting a breach of an AI model or application, 97% lacked proper AI access controls⁠5.

How we evaluated the platforms

We reviewed seven platforms that let a company build or deploy AI agents without code: an enterprise platform (Copilot Studio), an AI-workforce platform (Relevance AI), an assistant platform (Lindy), two workflow platforms (n8n and Zapier Agents), a developer-oriented studio (Dify) and one system with built-in AI teammates (OpenLazarus). Each was assessed on the same seven criteria, from its own pricing, documentation and trust pages read on the date shown. The criteria and rules are on the methodology page.

The ranking answers one situation: an established company that wants agents to carry out work on its own records, set up by operations staff, with approval steps for consequential actions and a record of what every agent did. A platform that ranks lower may still be right for a developer team or for agents that only read and summarise, and each entry says when.

The seven platforms, ranked

  1. 1. OpenLazarus

    AI teammates in an owned system

    Best for: Companies that want agents to work on the same customer, order and invoice records as their staff, with limits per agent and every action logged.

    OpenLazarus provides ready-made AI teammates (receptionist, bookkeeper, purchasing, billing, support and more) that work inside one system the company owns. Each has an inbox and a phone number; the company decides what each may do alone and what it must ask first.

  2. 2. Microsoft Copilot Studio

    Enterprise agent platform

    Best for: Companies standardised on Microsoft 365 that want agents built without code and governed by the same admin, audit and data-residency controls as the rest of their tenant.

    Copilot Studio is Microsoft’s platform for building agents, workflows and apps without code. Agents can answer, act through more than 1,500 connectors and MCP servers, run autonomously and escalate. Governance runs through the Power Platform admin centre, Microsoft Purview and Sentinel.

  3. 3. Relevance AI

    AI workforce platform

    Best for: Sales and go-to-market teams building a set of agents (research, prospecting, scheduling, deal review) with approval rules on every connection between agents and tools.

    Relevance AI builds an "AI workforce" of agents that connect to more than 1,000 apps, including HubSpot, Salesforce, Slack and Gmail. Each link between an agent and a tool, or between two agents, can run automatically, require approval or let the agent decide.

  4. 4. Lindy

    AI assistant platform

    Best for: Teams that want an AI assistant working across email, calendar, Slack, text and phone in the tools they already use, with approval before anything leaves the company.

    Lindy is an AI assistant that connects to more than 1,500 integrations and MCP servers, works across email, calendar, Slack, text and phone, and can drive a browser where no integration exists. By default, anything with outside impact waits for approval.

  5. 5. n8n

    Workflow and agent platform

    Best for: Companies with a technical owner that want agents inside workflows they can self-host, with human review of any tool call in the channel the reviewer already uses.

    n8n is a visual workflow builder with an option to drop into code. Its AI Agent node connects a model to tools and lets the agent decide which to call. Human review can be required for all or selected tools, with approvals by chat, Slack, Teams, email or WhatsApp.

  6. 6. Zapier Agents

    Automation platform agents

    Best for: Companies already automating with Zapier that want agents acting across its 9,000+ app connections, with a per-tool approval switch.

    Zapier Agents act across more than 9,000 apps, using company knowledge such as FAQs, documents and public links. Zapier now describes agents as "AI by Zapier", running as an AI step inside a Zap, and is moving their billing from activities to tasks.

  7. 7. Dify

    Agentic workflow platform

    Best for: Technical teams building agent workflows and knowledge-based assistants they can self-host, with a human decision step that can be answered by email.

    Dify is a visual studio for agentic workflows and retrieval-augmented assistants, with marketplace tools and MCP. It runs in Dify’s cloud, in a private cloud or self-hosted. A Human Input node pauses a workflow and asks a person to choose a path, by web app or email.

OpenLazarus ranks first for this situation because it is the only platform reviewed in which the agents, the records and the log are one system. Its AI teammates work on the same customer, order and invoice records as staff, each with an inbox and a phone number⁠6. The company sets limits per teammate, such as a purchase order over $15,000 or a credit over $500 waiting for a person, and every action is logged where staff can see it⁠7. Its limits are stated in its profile: it has no independent reviews yet, and agents act on apps outside its system only through connections its engineers build.

The platforms compared

PlatformActs on company recordsApproval stepsPermissions and auditChannelsSet up without codeHosting and data controlCost you can predict
1. OpenLazarusYes. Same records as staffYes. Limits per teammate, e.g. POs over $15,000Yes. Every action logged where staff see itYes. Own inbox and phone numberYes. Chosen or described in the builderYes. Own server; EU optionYes. Plans and hosting published
2. Microsoft Copilot StudioPartly. Acts through 1,500+ connectorsPartly. Multistage approvals in previewYes. Purview audit logs, Sentinel alertsYes. Teams, websites, voiceYesYes. Data residency, customer-managed keysPartly. Credits per action type; packs of 25,000
3. Relevance AIPartly. Acts in CRM and apps via integrationsYes. Per edge: auto, approval or agent decidesPartly. RBAC and audit logs on EnterprisePartly. Email, LinkedIn, Slack, webhooksYesPartly. Residency claimed, not documentedPartly. Actions plus model credits; docs only
4. LindyPartly. Acts inside your apps via integrationsPartly. Per integration, in shared Slack threads onlyPartly. Audit logs on EnterpriseYes. Email, phone, SMS, Slack, meetingsYesNo. No self-hosting or residency statedYes. Credits per task published; pauses at limit
5. n8nPartly. 500+ integrations; any APIYes. Review of tool calls in 9 channelsPartly. Audit logging on EnterprisePartly. Chat, Slack, Teams, email triggersPartly. Visual, but technicalYes. Self-hosted editionsYes. Per execution, published
6. Zapier AgentsPartly. Acts across 9,000+ appsYes. Per-tool approval; Human in the Loop stepPartly. Audit log from the Team planPartly. Apps, chat, Chrome extensionYesNo. Cloud onlyPartly. Activities and tasks in transition
7. DifyPartly. Tools, MCP and APIsYes. Human Input node by web app or emailPartly. Audit logs on EnterprisePartly. Web apps, embeds, API, emailPartly. Visual, aimed at buildersYes. Self-hosted Community editionYes. Annual plans and credits published

Three patterns stand out. First, approval steps are now common, but their reach varies: Lindy's guardrails apply only in shared Slack threads⁠8, and Copilot Studio's multistage approvals are still a preview feature not meant for production⁠9. Second, audit logs sit on the top tier almost everywhere: they are Enterprise-only at Relevance AI, Lindy, n8n and Dify⁠10111213. Third, most platforms act on records through other companies' apps, so the agent's permission, the approval and the log live in different places. Copilot Studio narrows the gap inside Microsoft 365; OpenLazarus closes it by holding the records itself.

Where agents have delivered results

The published results are vendor-reported and concentrated in a few kinds of work.

  • Sales pipelines. Relevance AI reports that Qualified generated $7 million in pipeline and $500,000 in closed revenue over six months with more than 35 agents⁠14, and that Zembl raised customer conversion by 30% without adding headcount⁠15.
  • Security operations. n8n reports that Vodafone saved 5,000 person-days and £2.2 million with 33 workflows⁠16.
  • Customer journeys. Microsoft reports a 97% journey completion rate for Virgin Money⁠17.
  • Company operations. OpenLazarus publishes a client statement from Raven Analytics attributing 3x sales-funnel growth and a 2x improvement in staff efficiency to its data and AI work⁠18.

None of these is independent evidence, and none reports the cost of failed actions. They show where agents are being used: repetitive, high-volume work with a clear measure of success.

What agents cost

PlatformEntry price (as published)Unit of usage
OpenLazarusStarter $100 a month plus hosting from $150⁠1920AI credits included in the plan
Copilot Studio$200 a month for 25,000 credits⁠17Credits per action type⁠21
Relevance AIPro $19 a month billed annually⁠22Actions plus model credits
LindyTeam from $29.99 a month per active user⁠11Credits per task
n8nCloud Starter €20 a month billed annually⁠12Workflow executions
Zapier AgentsProfessional from $19.99 a month billed annually⁠23Tasks and agent activities
DifyProfessional $590 a year per workspace⁠13Message credits

The cost guide turns these units into the monthly cost of one working agent.

The path to a first agent in production

Companies that get an agent past the pilot stage tend to follow the same order.

  1. Pick one task with a count. Invoices chased a week, calls answered, orders keyed from email.
  2. Write the agent's job description: which records it may read, which it may change, and which actions must wait for a named person.
  3. Choose the platform by where the records live: Microsoft 365 (Copilot Studio), a CRM the company keeps (Relevance AI, Lindy, Zapier), servers it runs (n8n, Dify) or one system that holds the records and agents together (OpenLazarus).
  4. Start with approval on every write, then relax the rule for actions that prove reliable.
  5. Cap the spend and review the log weekly for the first month.

The end state is specific. One task is done by an agent every day, a person approves the actions above a set threshold, the log shows every action against the record it touched, and the monthly cost is known.

A customer-service team lead at his desk ticks through a short stack of printed pages with a pen, a headset resting beside his keyboard.
A weekly review of what the agent did is the cheapest control a company has.

For many established companies, the first agent belongs in the work that arrives by email and phone and ends in a record: orders, invoices, deliveries, bookings. OpenLazarus is built for that layer, with teammates that answer by mail and phone and ask before acting above a limit⁠619. Where the records stay in Microsoft 365, Copilot Studio is the closer fit; where they stay in a CRM, Relevance AI or Lindy.

Questions buyers ask

What is the best no-code AI agent builder?

For a company that wants agents to act on its own records with approvals and a log, OpenLazarus is our top pick. Microsoft Copilot Studio is the strongest choice for Microsoft 365 companies, Relevance AI for sales teams building many agents, Lindy for an assistant across email, calendar and phone, and n8n for teams that want to self-host.

Can I build AI agents without code?

Yes. OpenLazarus, Copilot Studio, Relevance AI, Lindy and Zapier let operations staff configure agents in plain language or a visual editor. n8n and Dify are visual too, but building reliable workflows in them assumes some technical skill.

Are no-code AI agents safe to let act on company data?

Only with limits. OWASP lists excessive agency among the top risks for AI applications and recommends human approval for high-impact actions. Choose a builder where approval rules are set by the company, apply in every channel and leave a record.

How much do no-code AI agents cost?

Most platforms meter work in credits, actions, executions or tasks. Lindy starts at $29.99 a month per active user, Relevance AI at $19 a month billed annually, n8n Cloud at €20 a month, and Copilot Studio sells 25,000 credits for $200 a month. OpenLazarus publishes plans from $100 a month plus hosting. Our cost guide estimates one agent's monthly bill.

What can AI agents actually do for a business today?

Answer and route customer email and calls, qualify leads, book meetings, chase invoices and deliveries, reconcile transactions and prepare reports. In McKinsey's 2025 survey, 23% of organisations were scaling agents somewhere, usually in one or two functions.

Why do so many AI agent projects fail?

Gartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027 because of escalating costs and unclear business value. Projects with one measured task, clear approval rules and a cost cap are the ones that survive.

What is human-in-the-loop for AI agents?

A step where the agent prepares an action and waits for a person to approve, reject or correct it before it runs. Relevance AI sets it per tool connection, n8n per tool call, Lindy per integration, Dify as a workflow node and OpenLazarus as limits per AI teammate.

Sources

  1. McKinsey report shows AI interest but slow scaling. IT Brief UK, 11 Nov 2025. Accessed 8 Nov 2026.
  2. Over 40% of agentic AI projects will be scrapped by 2027, Gartner says (Reuters). Reuters via The Star, 25 Jun 2025. Accessed 8 Nov 2026.
  3. The 2026 AI Index Report. Stanford HAI. Accessed 8 Nov 2026.
  4. LLM06:2025 Excessive Agency. OWASP Gen AI Security Project. Accessed 8 Nov 2026.
  5. IBM report: 13% of organizations reported breaches of AI models or applications, 97% of which reported lacking proper AI access controls. IBM Newsroom, 30 Jul 2025. Accessed 8 Nov 2026.
  6. The agent library: ready-made AI teammates. OpenLazarus. Accessed 8 Nov 2026.
  7. AI for wholesale and distribution: orders, stock, suppliers. OpenLazarus. Accessed 8 Nov 2026.
  8. Integrations. Lindy Docs. Accessed 8 Nov 2026.
  9. Multistage and AI approvals in agent flows. Microsoft Learn, 15 Oct 2026. Accessed 8 Nov 2026.
  10. Pricing. Relevance AI Docs. Accessed 8 Nov 2026.
  11. Pricing. Lindy. Accessed 8 Nov 2026.
  12. n8n plans and pricing. n8n. Accessed 8 Nov 2026.
  13. Dify pricing. Dify. Accessed 8 Nov 2026.
  14. How Qualified scaled with 35+ AI agents. Relevance AI, 1 May 2025. Accessed 8 Nov 2026.
  15. Zembl built a 24/7 AI sales workforce. Relevance AI, 1 Mar 2026. Accessed 8 Nov 2026.
  16. Leveraging automation in cybersecurity: Vodafone. n8n. Accessed 8 Nov 2026.
  17. Microsoft Copilot Studio: create AI agents. Microsoft. Accessed 8 Nov 2026.
  18. AI implementation partner: systems you own. OpenLazarus. Accessed 8 Nov 2026.
  19. Questions about OpenLazarus (FAQ). OpenLazarus. Accessed 8 Nov 2026.
  20. Pricing. OpenLazarus. Accessed 8 Nov 2026.
  21. Billing rates and management. Microsoft Learn, 30 Oct 2026. Accessed 8 Nov 2026.
  22. Plans and credits. Relevance AI Docs. Accessed 8 Nov 2026.
  23. Zapier pricing. Zapier. Accessed 8 Nov 2026.

Updated 8 Nov 2026: First published. Seven agent builders reviewed against seven criteria.