As workflow automation has shifted from simple point‑and‑click integrations to AI‑driven orchestration, the tools on the market have matured. Make (formerly Integromat) is one of the platforms leading this shift. With its visual canvas, deep data manipulation, and new AI agent features, Make positions itself as a powerful alternative to tools like Zapier.
This review explores how Make works in 2026, what the pricing structure looks like, its strengths and limitations, and when choosing Make over Zapier makes sense.
Curious how it stacks up against Willo? Check out our comparison between Make and Willo.
What is Make?
Make is a cloud‑based automation platform that lets you build scenarios—visual workflows that connect apps, transform data and trigger actions across multiple services. A scenario is built by dropping modules representing triggers, actions or operations onto a canvas and connecting them with lines. Unlike linear automation tools that only support a trigger followed by actions, Make allows branches, loops, routers, error handlers, and data transformations. A trigger module fires first (for example, when a new row is added to a database), and then action modules perform tasks like sending a message or updating a record. Users map fields visually between modules and can split workflows using routers or iterate through lists. This level of control allows multi‑step processes, conditional logic and retries that run without breaking the entire scenario.
While the canvas looks user‑friendly, the platform is highly technical under the hood. It gives you granular access to data structures, arrays and API responses, and offers the ability to run custom JavaScript or Python via the Make Code App (costing 2 credits per second of execution). Early in 2026 Make introduced AI Agents, autonomous entities that live inside the scenario builder. They analyse inputs, choose appropriate tools and adapt within the workflow while showing their reasoning in a panel on the canvas. These agents are transparent—you can see why they take a path, chat with them in‑canvas to refine behaviour, and give them multimodal inputs like PDFs or images. The platform also includes AI integration modules for sentiment analysis, summarisation, translation and more, with the option to bring your own API key.
Integrations and ecosystem
Make supports over 3,000 app integrations, including popular SaaS tools, databases, communication channels and emerging AI models. Each integration exposes granular functions—beyond simply sending data from one app to another—allowing you to insert or transform records, fetch lists, run searches or trigger webhooks. The platform’s MCP (Model Context Protocol) server allows AI models to interact with business systems securely by passing context between modules. Additionally, a Library of Agents launched in 2026 provides ready‑made agent examples for common workflows, such as inventory management or research tasks, which teams can adapt and share.
Make also released Make Grid, an observability tool that maps scenarios and their connections across an organisation, making it easier to identify dependencies and orphaned workflows. This enhances governance for enterprise users.
Pricing and Plans
Make’s pricing is based on credits—each module action in a scenario consumes one credit (two credits per second for code execution). Credits are purchased in monthly allowances; once used, additional runs incur overage fees. Pricing options for 10 k credits per month (billed monthly) include:
| Plan | Price per month (10 k credits) | Key inclusions |
| Free | $0 | 1,000 credits/month, visual workflow builder, over 3,000 apps, routers & filters, customer support, runs every 15 minutes |
| Core | $10.59 | Everything in Free plus unlimited active scenarios, minute‑level scheduling, increased data transfer limits and access to the Make API |
| Pro | $18.82 | Everything in Core plus priority scenario execution, custom variables and full‑text execution log search |
| Teams | $34.12 | Everything in Pro plus teams & roles and the ability to create and share scenario templates |
| Enterprise | Custom pricing | Everything in Teams plus custom functions, enterprise app integrations, 24/7 support, overage protection and advanced security features |
There is no time limit on the free plan, making it suitable for experimentation. Paid plans scale by allowing larger credit packages (up to millions of credits per month) and by enabling advanced AI features and deeper integrations.
Credit model considerations
An operation‑based pricing model can be cost‑effective for complex workflows because filters, routers, and branching logic all count as operations. Some reviewers note that the cost per execution can climb quickly when scenarios contain many modules or run frequently, especially when using AI agents that consume tens of credits per run. Make’s ability to run custom code and complex logic means it may handle more work per execution than task‑based pricing, but budgeting credits carefully is essential.
AI and Advanced Automation Features
One of the biggest differentiators for Make in 2026 is its native AI capabilities. Besides providing pre‑built AI modules for tasks like sentiment analysis, translation and summarisation, Make offers AI Agents that operate within scenarios. The next‑generation agents introduced in February 2026 include several innovations:
- Agents inside the canvas – Agents are built, run and debugged in the same canvas as scenarios, letting you see their logic alongside your deterministic modules.
- Radical transparency – A Reasoning Panel shows each decision the agent makes and the tools it calls, giving you control over inputs and outputs.
- In‑canvas chat – You can converse with your agent directly on the canvas to test and refine behaviour without leaving the workflow editor.
- Multi‑modal support – Agents can accept and generate files (PDFs, images, CSVs) as part of a scenario, turning unstructured data into structured workflow assets.
- Shareability and templates – A Library of Agents allows teams to share and reuse agents built for specific business processes, accelerating adoption.
Beyond agents, Make’s AI integration framework emphasises orchestration rather than single‑tool AI features. A guide from January 2026 explains that AI integration builds visual workflows that trigger on business events, route tasks to the right model, transform outputs and maintain visibility. This process solves four common problems: eliminating manual prompting, ensuring inputs are filtered and enriched before AI processing, transforming AI outputs into structured formats, and maintaining observability with module‑level tracking. Routers, filters and conditional logic determine which AI model handles each task, enabling sophisticated routing based on task type, modality, cost and compliance. By combining AI modules with Make’s existing automation features, users can build powerful agentic workflows that connect multiple AI models and business systems.
Strengths of Make
Visual and powerful – Make’s scenario canvas lets you see your entire workflow at once and design complex logic with routers, loops, error handlers and data transformations. This visual approach reduces the “black box” feel of automation and makes debugging easier.
Deep integrations – While Make offers fewer app connections than some competitors, the integrations expose rich functionality. Users can manipulate data, call APIs directly and manage data structures with precision. The platform’s credit model allows you to run multi‑step scenarios without paying for each action individually.
Native AI and agents – Make’s built‑in AI Toolkit and AI Agents give you access to modules for sentiment analysis, translation, classification and summarisation. Agents operate transparently inside scenarios, can handle multimodal data and support real‑time chat for refinement.
Flexible pricing – The generous free tier of 1,000 credits allows meaningful testing. Paid plans offer predictable costs based on operations rather than tasks, which can be more economical for complex workflows.
Observability and governance – Tools like Make Grid map workflows across the organisation, and the platform keeps detailed execution logs and reasoning panels for agents, aiding compliance and debugging.
Scalable AI orchestration – Make’s AI integration framework emphasises routing, transformation and observability, enabling you to build multi‑model pipelines with human‑in‑the‑loop decision points.
Limitations and Considerations
Learning curve – Despite the friendly interface, Make has a steep learning curve. Building complex scenarios requires understanding arrays, webhooks and APIs. Some reviews describe the experience as learning a programming language efficiently. Non‑technical users may prefer simpler tools for basic automations.
Credit consumption – Make counts every module execution as a credit. Workflows with many branches or AI agents can consume credits quickly. Budgeting and optimisation are necessary to avoid unexpected costs.
Error handling – Reviews note that error messages can be unclear and that troubleshooting complex scenarios can be challenging. While visual debugging helps, novice users may still struggle.
AI agent cost and maturity – AI Agents (especially multi‑modal ones) use multiple credits per run and are still evolving. The technology is powerful but may require experimentation to achieve stable results.
Not a development platform – Make excels at orchestrating workflows between existing systems but does not replace building applications. It lacks native front‑end components; thus, it is best used as an automation layer.
When Make Beats Zapier
Zapier remains the household name in no‑code automation. It offers more than 8,000 app integrations and is praised for its ease of use. However, Make outperforms Zapier in several situations:
Complex workflows and data processing
Make supports conditional branches, loops, routers and error handlers that let you split workflows, retry failed steps, and transform data within a single scenario. While Zapier has added loops and error handling, it still operates primarily on linear triggers and actions. If your process involves multiple decision points—such as routing leads by region, batch updating records or cleaning data before sending—it will be easier to model in Make.
Advanced AI and agents
Zapier integrates with many AI tools and recently introduced its own AI agents, but these features rely on third‑party services. Make offers native AI modules and agent functionality with transparent reasoning panels and in‑canvas chat. For workflows where AI must adapt, analyse unstructured data or be combined with deterministic steps, Make’s AI toolkit is more powerful.
Pricing for multi‑step automation
Zapier uses a task‑based pricing model: each step counts as a task. A five‑step Zap consumes five tasks per run, which can become expensive. Make’s credit‑based model charges by module execution, but operations such as filters, routers or iterators may be less costly than separate tasks. The free plan (1,000 credits) is more generous than Zapier’s free plan (100 tasks), and the Core plan starts at roughly US$10.59 compared with Zapier’s Professional plan at US$19.99. For workflows with many steps or branching logic, Make typically offers better cost efficiency.
Deeper integrations
Zapier’s strength is breadth: it supports more than 8,000 apps. However, the depth of its integrations is limited; many triggers and actions are simple. Make’s modules often expose more granular operations, giving you finer control over how data is queried, transformed and written. If you need to manipulate nested objects, handle arrays or call custom endpoints, Make’s integration depth is advantageous.
Best use cases
According to user discussions summarised in impartial reviews, Zapier excels at simple use cases like lead capture, notification workflows and basic data syncing. Make shines in complex approval workflows, bulk operations, data processing and scenarios requiring error handling and retries. The choice depends on whether you prioritise ease of setup or flexibility and control.
Verdict: Is Make Worth It in 2026?
Make has evolved into a sophisticated automation platform that combines a visual canvas with deep data manipulation and native AI. The 2026 release of AI Agents demonstrates the company’s focus on transparency and control—agents run inside the workflow, reveal their reasoning and accept multimodal inputs. The platform’s pricing is competitive, especially for complex scenarios, and the free tier is generous.
However, Make is not for everyone. Non‑technical users may find the learning curve steep. The credit model requires careful planning, and AI agents can consume credits quickly. If your automation needs are simple—connecting one app to another or running straightforward sequences—Zapier or other beginner‑friendly tools may provide faster value. But if you’re orchestrating multi‑step workflows, transforming data, integrating AI models or needing granular control over each step, Make is one of the most powerful platforms available.
Ultimately, Make is best suited for operations teams, marketers, RevOps professionals and technical users who want to build automation infrastructure without writing code. In 2026 it offers a compelling blend of visual design, advanced logic and AI integration that often beats traditional tools when workflows demand sophistication.
