No-code agent builders let business teams create agents without writing backend code. Lindy, Relevance AI and Microsoft Copilot Studio each take a different route, and Xagent takes another. The right choice depends on the work you want to hand over, the systems it touches, the models you want to use and how you prefer to pay.
What should you compare?
Compare five things: how you build an agent, which systems it can reach, which models it can use, what you can see while it runs, and how pricing scales. Feature lists change every month. These five questions decide whether an agent will still be useful after the pilot.
All vendor facts below come from each vendor’s own pages, checked in October 2026. Check them again before you buy, because plans and limits change often.
Lindy: an AI teammate for the whole team
Lindy presents itself as an AI teammate that plugs into your tools and takes work off the team’s plate. Its use cases span marketing, sales, support, operations and finance. Its pricing is per user, with credits. As of October 2026, every active user is billed from US$29.99 a month for 3,000 credits each, and credits are pooled across the team. An Enterprise plan adds security, compliance and admin features.
Lindy fits teams that want an AI teammate inside their chat and everyday tools, and that are comfortable with per-user pricing.
Relevance AI: an agent workforce for operations teams
Relevance AI is aimed at teams building a set of agents for business processes such as sales research and account enrichment. Its site highlights monitoring, agent tracing, evaluations and cost visibility. Its pricing page lists SSO, access roles and logging among its enterprise features.
Relevance AI fits operations teams that want many process agents, with evaluations and monitoring as part of the product.
Microsoft Copilot Studio: agents inside the Microsoft stack
Copilot Studio builds agents within Microsoft 365 and the Power Platform. As of October 2026, Microsoft says you can choose default or custom models, or models from Azure AI Foundry. It also lists more than 1,500 prebuilt data connectors and support for MCP servers. Its documentation describes agent flows with an authoring experience similar to Power Automate.
Copilot Studio fits organisations already standardised on Microsoft 365, Dynamics and Azure, where one vendor, one tenant and one admin centre matter most.
How does Xagent approach it?
Xagent starts from a plain-language request. You describe a task, Xagent writes a plan shown as an execution graph with one card for each step, and then it runs the plan with tools. Every tool call and result is visible while the task runs, along with the token count. A running task can be paused.
A task that works can be saved as an agent. The agent keeps its role, model, tools and knowledge, and can be run again or scheduled. Five specialist roles ship in every workspace: support, growth, planner, knowledge and studio. Templates cover a support chatbot, inbound leads, LinkedIn posts, email, content, an inbox manager, slides and documents. Our post on your first agent from a template shows how that works.
On models, Xagent works with open models and API providers, including any OpenAI-compatible endpoint. It can also run on models self-hosted through Xinference, the inference platform behind it. Native connectors cover Google, Microsoft, Meta and LinkedIn, and other systems connect through MCP servers.
How do they compare side by side?
| Dimension | Lindy | Relevance AI | Copilot Studio | Xagent |
|---|---|---|---|---|
| Typical user | Teams that want an AI teammate in chat | Operations teams | Microsoft-standardised organisations | Operations, marketing, sales and support leads |
| How you build | Ask the AI teammate in chat and tools | Build agents for business processes | Agent builder and agent flows in Microsoft 365 | Plain-language request, then save it as an agent |
| Systems | Works across common apps | Large integration library | 1,500+ prebuilt connectors, MCP servers | Google, Microsoft, Meta, LinkedIn, plus MCP servers |
| Models | See vendor | See vendor | Default, custom or Azure AI Foundry models | Open models, API providers, any OpenAI-compatible endpoint, or self-hosted through Xinference |
| Pricing basis | Per user with credits, from US$29.99 | See vendor | Microsoft licensing | From US$59 a month for 2 users, unlimited agents |
| Where it runs | Vendor cloud | Vendor cloud | Microsoft cloud | Xagent cloud, or self-hosted on Enterprise |
How should you think about cost?
Pricing models differ, so a headline price says little on its own. Lindy charges per user with credits. Microsoft prices Copilot Studio within its own licensing. Xagent’s Pro plan is US$59 a month for 2 users, 5,000 actions and triggers and 10,000 AI credits. Team is US$299 a month for 10 users, and Enterprise is priced with sales. Details are on the Xagent pricing page.
Start with your expected run volume. Model it against each shortlisted plan, then add model usage, connector or integration fees, support and the time your team will spend running it. Work out the break-even point from a pilot, not from a generic run count.
Which one should you choose?
- Choose Lindy if you want an AI teammate that works inside your chat and everyday tools.
- Choose Relevance AI if an operations team wants to build and evaluate many process agents.
- Choose Copilot Studio if your organisation runs on Microsoft and wants agents managed in that tenant.
- Choose Xagent if the people who own the work want to describe it in plain language, see every tool call, and choose their own models, including self-hosted ones.
The best test is a pilot. Pick one task your team repeats every week and build it on two platforms. Measure how long it takes to build, how often a person has to step in, and what it costs at your real volume. If you are also weighing workflow tools, read Xagent vs Zapier and Make. To run your own task in Xagent, book a demo.
Questions
What is a no-code agent builder?
It is a tool that lets business users create AI agents without writing backend code. You describe or configure the agent, connect your apps and let it act on tasks.
Can Copilot Studio use models other than Microsoft’s?
As of October 2026, Microsoft says Copilot Studio can use default or custom models, or models available through Azure AI Foundry.
Can Xagent use our own models?
Yes. Xagent works with open models and API providers, including any OpenAI-compatible endpoint, and can run on models self-hosted through Xinference.
Is there a free version of Xagent?
No. Xagent plans start at US$59 a month for Pro. You can book a demo to see it on your own task first.
Try Xagent. See all use cases, or book a demo on your own workflow.
