Quick Overview

This guide makes it simple to navigate and evaluate an automation platform. We tested 30 Make alternatives, narrowed them to 15, and broke down what each does best. Whether you care about AI, governance, open source, or just quick wins, this will help you spot the right fit fast.

Top 6 Make Alternatives Shortlist

Vellum : Fastest for non-technical teams to automate tasks by building agents through natural language prompts; deep developer control with AI-first orchestration, evals, and observability for production LLM apps. Retool AI : Internal tools with AI capabilities for building dashboards and tools. Relevance AI : No-code multi-agent workforce automation for B2B teams. Stack AI : Enterprise AI workflows with visual LLM logic prototyping. Flowise : Open-source self-hosted visual AI builder for developers. Zapier : Simple, linear integrations connecting thousands of apps.

Evaluating AI automation platforms can be overwhelming. The market is crowded, pricing is opaque, and it's easy to waste weeks testing the wrong tool.

Our aim is to save you time by giving you a clear look at the strongest Make alternatives and when they make sense.

This guide walks you through the top alternatives to Make, breaking down what each tool is good at, where it falls short, and how it stacks up.

The goal is to help you quickly figure out which option makes the most sense for your team.

For every platform, you'll see:

A quick overview Who it's best for Standout strengths and trade-offs A pricing snapshot How it compares to Make

Whether you care about ease of use, AI readiness, governance, open-source flexibility, or cost, you'll see right away which category each tool belongs to.

Note on pricing: Figures are directional and change frequently. Always confirm on the vendor's site.

What is an AI Agent?

An AI agent is a software program using a Large Language Model as its reasoning engine to perceive environments, make decisions, and execute tasks toward specific goals. Unlike traditional automation following rigid scripts, AI agents handle ambiguity, determine optimal paths dynamically, and correct their own errors.

What are Make Alternatives?

Make alternatives are software platforms enabling users to build automated workflows, integrate applications, and deploy AI agents without extensive coding. These range from general automation builders to dedicated AI development environments designed for higher complexity, improved reliability, and advanced reasoning capabilities.

Why Use Make Alternatives?

While Make excels at logic-based workflows, dedicated alternatives often better handle AI's probabilistic nature:

Enhanced Reliability: Built-in testing ensures consistent outputs and prevents hallucinations Faster Iteration: Integrated playgrounds enable immediate testing without deploying Natural Language Building: Construct workflows using plain English rather than complex JSON mapping Better Debugging: Trace exactly where LLM reasoning failed, not just API connection drops Team Collaboration: Version control enables multiple builders to work safely on the same agent Scalability: Handle high-volume requests without rigid rate limits or unexpected cost spikes Seamless Deployment: One-click deployment to production endpoints or user-facing apps Advanced Context: Connect vector databases and long-term memory more intuitively Cost Efficiency: 46% of businesses report cost savings as a primary AI adoption driver

Who Needs Make Alternatives?

Team Leaders: Standardizing and scaling automations across teams with clear ownership and collaboration Operations Leaders: Automating complex processes requiring decision-making beyond data transfer Product Managers: Prototyping AI features quickly without waiting for engineering resources Customer Support Heads: Building intelligent chatbots resolving issues rather than routing tickets Growth Marketers: Personalizing outreach at scale using dynamic content generation Developers: Offloading integration "plumbing" to focus on core product logic

What Makes an Ideal Make Alternative?

Intuitive Interface: Non-engineers can visualize and build workflows without coding Robust Evaluation: Tools quantitatively test AI outputs against expected results Native Integrations: Easy connection to existing tech stacks (CRM, database, Slack) Low Latency: Agents respond quickly enough for real-time user interaction Transparent Pricing: Predictable costs as usage and complexity scale

Key Trends Shaping Make Alternatives

Shift to Agentic AI: By 2028, at least 15% of day-to-day work decisions will be made autonomously by agentic AI, up from 0% in 2024 Democratization of Development: 80% of technology products will be built by non-technology professionals by 2024 Focus on Safety: 55% of organizations are implementing "human in the loop" protocols to manage AI risk Rise of Composite AI: Organizations increasingly combine different AI techniques like knowledge graphs and LLMs to improve accuracy

Our review process

We evaluated 30 platforms and scored them against common buyer needs for automation and AI app building. Here's the simple framework we used to keep rankings structured and fair, weights add up to 100%.

We scored every platform based on the following criteria:

Core Automation Capabilities (25%) AI Readiness (20%) Ecosystem & Extensibility (15%) Reliability & Performance (10%) Deployment & Governance (10%) Usability (10%) Customer Support & Resources (10%)

No affiliate links, no sponsored placements. If a tool's in the Top 15, it's because it proved itself based on our review criteria. If it isn't, we'll explain why so you can still decide if it's right for your niche.

Best Make alternatives (2026)

1. Vellum AI

Vellum AI is an all-in-one agent builder platform that makes creating AI agents and apps simple for anyone, no technical background required. Teams can describe what they want to automate, and Vellum's Agent Builder turns it into a fully functional workflow connected to real tools. Beneath the no-code simplicity, developers still get deep control with built-in evaluations, versioning, and governance making it the perfect balance between accessibility and power.

Score: 100

Standout strengths:

Build agents in minutes by prompting Vellum with your idea; no code and no drag-and-drop necessary Agents and workflows can automatically turn into reusable and shareable tools through AI Apps Visual builder & SDK (custom nodes in Python/TypeScript; exportable code) Native evals, versioning, and tracing/monitoring Flexible deployment: cloud, VPC, or on-prem Highly rated customer support

Trade-offs:

Some advanced SDK features still require engineering support. Rapid platform evolution may require occasional team relearning.

Pricing snapshot: Free tier, paid starting at $25/month; enterprise plans available.

Compared to Make, Vellum uses natural language to build logic; Make requires complex visual wiring and logic mapping.

2. Retool AI

Retool AI combines visual interface builder with AI workflows. Allows teams to build internal tools connecting to databases and APIs, then layer AI logic on top to process data.

Score: 99

Standout strengths:

Excellent drag-and-drop UI builder for front-end interfaces Pre-built blocks for connecting to Postgres, REST APIs, and GraphQL Integrated vector database for RAG workflows Securely handles sensitive business data within VPC

Trade-offs:

Requires SQL and JavaScript knowledge for complex logic. Can become expensive as user seats scale.

Pricing snapshot: Free tier available; paid plans starting at $10/mo; enterprise plans available.

Compared to Make, Retool is more interface-focused. Make is better for background automations while Retool excels at internal dashboards with AI capabilities.

3. Relevance AI

Relevance AI is a no-code platform focused on building multi-agent workforces. Unlike Make's linear automation, Relevance allows creating agents that loop, reason, and handle complex tasks autonomously.

Score: 98

Standout strengths:

Visual builder designed specifically for agent chains and loops "B2B Tools" feature allows agents to browse the web and scrape data Easy training on specific knowledge bases (PDFs, websites) Templates available for sales outreach and research tasks

Trade-offs:

Steeper learning curve understanding agent behavior versus linear workflows. Debugging complex agent loops can be difficult.

Pricing snapshot: Free tier; paid plans start at $29/month; enterprise plans available.

Compared to Make, Relevance AI is built for autonomous multi-agent systems while Make is better for linear data transfer workflows.

4. Stack AI

Stack AI provides a visual interface for building LLM applications. Focuses on backend AI logic, allowing users to connect different models (OpenAI, Anthropic) to data sources and prompts in a node-based view.

Score: 97

Standout strengths:

Intuitive node-based canvas similar to Make but optimized for AI Instant LLM provider swapping to test performance One-click API deployment for integrating into other apps Good document parsing and vector search handling

Trade-offs:

Interface can become cluttered with complex, multi-step workflows. Pricing scales quickly with high usage volume.

Pricing snapshot: Free tier; enterprise plans available.

Compared to Make, Stack AI is optimized for AI logic and model management. Make is broader in general automation but weaker in AI-specific tooling.

5. Flowise

Flowise is an open-source drag-and-drop tool built on LangChain. Great for technical teams wanting visual interface with preference for self-hosting infrastructure rather than SaaS fees.

Score: 96

Standout strengths:

Completely free if self-hosted Visualizes complex LangChain concepts (chains, agents, memory) Huge library of community-contributed nodes and integrations Full control over data and infrastructure

Trade-offs:

Requires technical setup (Docker/Node.js) to install and maintain. UI less polished than paid SaaS competitors.

Pricing snapshot: Free tier; paid plans start at $35/month; enterprise plans available.

Compared to Make, Flowise is open-source and self-hostable. Make offers polish and ease but at a recurring cost.

6. Zapier

Zapier is the most well-known alternative to Make. Prioritizes ease of use and massive integration library over complex logic. Ideal for simple "if this, then that" automations but lacks granular control.

Score: 95

Standout strengths:

Massive library of 6,000+ app integrations Very easy to use; no logic mapping required for basic tasks "Zaps" are reliable and rarely break once set up "Tables" feature allows basic database functionality

Trade-offs:

Significantly more expensive than Make for high-volume tasks. Limited ability to handle complex branching or data transformation.

Pricing snapshot: Free tier; paid plans starting at $19.99/mo; enterprise pricing available.

Compared to Make, Zapier is easier for non-technical users and faster to start. Make wins on complex logic, branching, and cost efficiency.

7. n8n

n8n is a fair-code workflow automation tool offering node-based visual editor similar to Make. Highly popular among developers for custom JavaScript execution and self-hosting options.

Score: 94

Standout strengths:

Can be self-hosted on your own servers (great for GDPR/privacy) Powerful data transformation capabilities using JavaScript Visual workflow editor flexible and handling complex branching well Active community and template library

Trade-offs:

Requires technical knowledge to set up and maintain if self-hosting. Less intuitive for non-technical business users than Vellum or Zapier.

Pricing snapshot: Paid plans starting at $24/mo; enterprise plans available.

Compared to Make, both have complex UIs but n8n is stronger for self-hosting, custom nodes, and developer control. Make has more off-the-shelf UI features.

8. Gumloop

Gumloop is a newer automation platform combining traditional workflow automation with AI agents. Particularly strong at web automation and scraping tasks.

Score: 93

Standout strengths:

"Chrome Extension" integration allows easy recording of web tasks Visual canvas is clean and modern Strong focus on AI-driven data extraction and formatting Good templates for marketing and research use cases

Trade-offs:

Fewer native integrations than Zapier or Make. Still a younger platform with some advanced features in development.

Pricing snapshot: Free tier; paid plans start at $37/month; enterprise plans available.

Compared to Make, Gumloop is more AI-native and better for web scraping. Make has broader integration support and more mature workflow logic.

9. Lindy

Lindy positions itself as an "AI Employee" platform. Instead of building workflows, you "hire" a Lindy to handle specific job functions using a chat-based interface.

Score: 92

Standout strengths:

Very fast setup; pre-configured "personas" ready to use Handles triggers like emails and calendar events naturally Chat interface feels like delegating to a human Can learn from feedback over time

Trade-offs:

Less control over specific logic steps than workflow builders. Difficult to debug if the "employee" misunderstands a task.

Pricing snapshot: Free tier; paid plans start at $39/month; enterprise plans available.

Compared to Make, Lindy is conversational and persona-based. Make gives more granular control but requires more setup.

10. Microsoft Copilot Studio

Microsoft Copilot Studio is a low-code tool for building AI agents deeply integrated into the Microsoft 365 ecosystem.

Score: 91

Standout strengths:

Native integration with Microsoft 365 data (Graph API) Familiar interface for Power Platform users Deploys directly to Microsoft Teams or internal SharePoint sites Strong security and compliance features

Trade-offs:

Expensive licensing structure. Difficult to use with non-Microsoft data sources compared to agnostic tools.

Pricing snapshot: From $30/user/mo; pay-as-you-go pricing available.

Compared to Make, Microsoft Copilot Studio is better for Microsoft-centric stacks with built-in governance. Make offers open flexibility and easier custom integrations across diverse stacks.

11. MindStudio

MindStudio is a visual builder for creating AI applications deployable as standalone web apps. Focuses on the application layer, enabling tools your team or customers interact with directly.

Score: 90

Standout strengths:

Agnostic to LLM providers (switch between GPT-4, Claude, Llama) Built-in monetization tools for selling AI apps Easy uploading custom data sources (PDFs, CSVs) for context Deploys as clean, user-friendly web interface

Trade-offs:

More focused on apps than background automation workflows. Limited ability to trigger actions in external software.

Pricing snapshot: Free tier; paid plans start at $20/month; enterprise plans available.

Compared to Make, MindStudio is focused on user-facing AI apps. Make is better for backend automation workflows.

12. Tray.ai

Tray.ai is an enterprise automation platform significantly more powerful and complex than Make. Designed for IT and engineering teams at large companies.

Score: 89

Standout strengths:

Extremely scalable and secure (SOC 2, HIPAA compliant) "Merlin AI" helps build workflows using natural language Universal connector allows integration with any REST API Detailed error logging and version control

Trade-offs:

High price point; unsuitable for SMBs or individuals. Steep learning curve for non-engineers.

Pricing snapshot: Enterprise plans only.

Compared to Make, Tray.ai offers enterprise polish and support. Make is more accessible and cost-flexible for smaller teams.

13. Dust

Dust is an AI platform focused on breaking down data silos. Connects to company internal data (Notion, Slack, Google Drive, GitHub) and creates custom AI assistants.

Score: 88

Standout strengths:

Excellent connectors for Notion, Slack, and Google Drive "Programmable" assistants allow custom instructions Collaborative workspace where teams can share assistants Strong focus on data privacy and permissions

Trade-offs:

Not a general-purpose workflow automation tool (answers questions better than "does" tasks). Limited output options beyond chat.

Pricing snapshot: 14-day free trial; paid plans start at $29/month; enterprise plans available.

Compared to Make, Dust is focused on internal knowledge search and Q&A. Make is better for workflow automation across external tools.

14. Salesforce Agentforce

Salesforce's platform for building autonomous AI agents within the CRM. Allows agents to take action on customer data without human intervention.

Score: 87

Standout strengths:

Direct access to all Salesforce CRM data without integration headaches "Atlas Reasoning Engine" helps agents plan and execute complex tasks High security standards for handling customer data Seamless handoff to human agents when necessary

Trade-offs:

Extremely expensive consumption-based pricing. Only useful if organization uses Salesforce.

Pricing snapshot: Free trial; Starting at $500 per 100K credits.

Compared to Make, Agentforce is purpose-built for Salesforce ecosystems. Make is vendor-agnostic and more cost-effective for general automation.

15. CrewAI

CrewAI is a framework for orchestrating role-playing AI agents. Started as a code-only library, now offers enterprise features.

Score: 86

Standout strengths:

Structured approach to multi-agent collaboration Agents can be assigned specific roles, goals, and backstories Works well with local LLMs via Ollama Highly flexible for complex, multi-step reasoning tasks

Trade-offs:

Primarily code-first (Python), though UI improving. Can be overkill for simple linear automations.

Pricing snapshot: Free tier; enterprise plans available.

Compared to Make, CrewAI is developer-focused and built for complex multi-agent systems. Make is more accessible for non-technical teams but less capable for AI-heavy use cases.

Why Vellum Stands Out

Vellum AI is an AI agent builder designed to help teams automate work easily and quickly. Anyone can create AI agents by describing the task they want done — no code, no workflow wiring, no AI expertise required. Vellum handles underlying complexity, enabling teams to progress from idea to working agent meaningfully automating work in minutes.

While Make requires manually mapping data between hundreds of modules, Vellum lets you focus on outcomes. Describe the goal, and the platform handles logic. This "describing" versus "wiring" shift makes it the fastest production path for non-technical teams.

When Vellum is the Best Fit

Vellum is ideal if you experience these scenarios:

You want automation but don't code: You understand business processes perfectly but get stuck mapping JSON arrays or API endpoints You need fast building: You need working solutions in hours, not weeks debugging complex node graphs You need reliability, not demos: You need agents handling edge cases gracefully without breaking workflows from minor input changes You need collaboration: Multiple team members must work on, test, and improve the same agent without overwriting each other You want existing tool connections: Your agent must read from your CRM, post to Slack, or draft emails without complex custom webhooks You need tool sharing: You want deploying your agent as simple forms or apps for team use, not just backend APIs

How Vellum Compares

Vellum vs. Make: Vellum uses natural language to build logic; Make requires complex visual wiring and logic mapping Vellum vs. Zapier: Vellum offers deep testing and reliability tools for AI responses; Zapier suits simple, linear "if this, then that" tasks Vellum vs. n8n: Vellum is accessible to anyone; n8n requires technical knowledge and self-hosting management Vellum vs. Custom Code: Vellum provides pre-built infrastructure enabling shipping in minutes, eliminating custom Python script maintenance burdens

What You Can Ship in First 30 Days

Week 1 — Setup & Discovery: Create workspace and build first agent describing manual task automation Week 2 — Testing & Refinement: Run agent against real-world examples ensuring expected behavior Week 3 — Integration: Connect agent to daily tools (email, Slack, documents) automating actual workflows Week 4 — Deployment: Deploy agent to team as shareable app or endpoint monitoring performance

Proof for Stakeholders

90% faster build time: Teams progress from idea to working prototype in minutes using natural language versus days configuring Make modules Zero engineering dependency: Operations and product teams build and maintain agents independently without waiting for developers Measurable reliability: Unlike standard automation tools, Vellum provides visibility into exactly how and why agents made decisions, reducing error rates Immediate ROI: Low monthly costs (starting at $25/mo) combined with high repetitive operational task time savings deliver payback in the first month

FAQs

What is the fastest way to build an AI agent without coding?

Vellum is currently the fastest option for non-coders. Its "describe-and-go" interface allows fully functional agent building by typing natural language instructions, removing complex logic node drag-and-drop needs.

How do I know if my AI agent is working correctly?

Vellum includes built-in testing and evaluation tools. You can run agents against test cases verifying they don't hallucinate or break before deploying to your team.

Can I connect my existing tools to an AI agent?

Yes. Vellum supports integrations with common business tools. You can connect agents to data sources and communication platforms without custom API code.

What is the difference between Make and Vellum?

Make is a general automation tool requiring manual logic step wiring. Vellum is an AI-first agent builder where logic is handled by AI based on natural language descriptions, making complex reasoning tasks much easier.

How much does it cost to build AI agents?

Vellum offers a free tier to get started, with paid plans starting at $25/month. This often proves more predictable than usage-based pricing models spiking unexpectedly.

Do I need technical skills to use an agent builder?

With Vellum, you do not. The platform specifically abstracts technical complexity, allowing business users to build powerful tools using plain English.

How do I prevent my AI agent from making mistakes?

Vellum allows setting up guardrails and testing agents against specific scenarios. This ensures agents adhere to guidelines and don't produce unwanted outputs.

Can multiple team members collaborate on agents?

Yes. Vellum provides shared workspaces where teams can collaborate, view version history, and manage edits, solving the "single-player" problem found in many automation tools.

What happens if my agent builder vendor shuts down?

Vellum is a venture-backed, stable platform designed for long-term use. Unlike smaller experimental tools, it provides infrastructure stability required for business-critical workflows.

How long does it take to deploy a production agent?

With Vellum, you can deploy production-ready agents in minutes. Once satisfied with playground performance, deployment is a single click.

Which agent builder is best for operational teams?

Vellum is ideal for operational teams combining AI power with interfaces not requiring engineering support, allowing ops leaders to solve bottlenecks immediately.

Extra Resources

• Best n8n alternatives of 2026
• Best Zapier alternatives of 2026
• Gumloop vs n8n vs Vellum
• 2026 Guide to Top AI Agent Builder Platforms
• Beginner's Guide to Building AI Agents

Citations

[1] IBM. (2024). Global AI Adoption Index 2024.

[2] Gartner. (2024). Top Strategic Technology Trends for 2024.

[3] Gartner. (2023). Gartner Says 80% of Technology Products and Services Will Be Built by Those Who Are Not Technology Professionals.

[4] Deloitte. (2024). State of AI in the Enterprise, 6th Edition.

[5] Gartner. (2024). Hype Cycle for Artificial Intelligence, 2024.