Which is better, Relevance AI or Make?

Relevance AI suits users who value no-code/low-code builder with multi-model routing (claude, gpt, gemini) instead of vendor lock-in, while Make is preferred when visual builder makes complex branching logic genuinely readable, not just a chain of linear steps matter most. Pick based on your primary workflow.

Is Relevance AI or Make cheaper?

Relevance AI is freemium, Make is freemium. Check each official site for current tiers.

Relevance AI vs Make

A side-by-side look at Relevance AI and Make — pricing, features and where each one wins. Both are reviewed independently on Curata AI.

	Relevance AI	Make
Summary	Enterprise platform for building, orchestrating and governing an 'AI workforce' of autonomous agents across sales, support, marketing and ops.	Visual AI automation platform for building workflows and AI agents across 3,000+ connected apps.
Pricing	Freemium	Freemium
Category	Automation	Automation
Platforms	Web, API	Web
Key features	No-code/low-code agent builder Multi-model routing (Claude, GPT, Gemini and others) by cost/performance Multi-agent orchestration into coordinated workforces Evaluation framework tracking live pass rates and drift Real-time tracing, audit logs, human-in-the-loop approvals and cost visibility 2,000+ integrations (Salesforce, HubSpot, Gmail, Slack, Databricks, Snowflake)	Visual Scenario Builder (drag-and-drop) AI Agents & Prompt-Based Building 3,000+ App Integrations Routers & Complex Branching Logic Custom Variables & Full-Text Log Search Enterprise Governance (SSO, SOC 2/3)
Pros	No-code/low-code builder with multi-model routing (Claude, GPT, Gemini) instead of vendor lock-in Genuine free tier (200 Actions/month) — rare among enterprise-grade agent platforms Real production governance: tracing, audit logs, human-in-the-loop approval and cost visibility 2,000+ integrations cover most existing sales, CS and ops stacks Enterprise trust signals — customers include Canva, KPMG, Databricks, Autodesk and Confluent	Visual builder makes complex branching logic genuinely readable, not just a chain of linear steps 3,000+ app integrations cover most real-world automation needs out of the box AI Agents extend Make beyond point-to-point triggers into multi-step, AI-orchestrated processes Real free tier (1,000 credits/month, 2 active scenarios) makes it easy to validate before paying Enterprise-ready governance (SSO, SOC 2/3) supports larger, regulated organizations
Cons	September 2025 pricing overhaul split billing into Actions + Vendor Credits, which reviewers say makes real cost harder to predict at scale Action overages and retry billing have caught some teams off guard on their first high-volume billing cycle Shared workspace model makes credential isolation difficult for agencies managing multiple client environments Some users report slow or impersonal customer support response times Real learning curve to build and maintain reliable multi-step agents	Pricing is credit-based, so heavier or more complex scenarios can consume a monthly allowance faster than a simple task count suggests Steeper learning curve than a purely linear automation tool once scenarios use routers and complex branching The Free plan's 2-scenario cap and 15-minute run interval are restrictive for anything beyond testing Some advanced features (custom functions, full enterprise app integrations) are reserved for the Enterprise tier

Read the full Relevance AI review

Relevance AI markets itself as 'the home of the AI Workforce' — a platform for building autonomous AI agents that handle work across sales, customer success, marketing, customer support, operations, HR and research, rather than hiring additional headcount. A no-code/low-code builder creates specialist agents, multi-model routing sends each task to the most cost-effective LLM (Claude, GPT, Gemini and others), and orchestration coordinates multiple agents into a team for complex workflows. Production tooling includes an evaluation framework that samples live runs and tracks pass rates, real-time tracing, audit logs, human-in-the-loop approvals and cost visibility, plus a shared context layer for consistent tone across agents. It connects to 2,000+ integrations including Salesforce, HubSpot, Gmail, Slack, Databricks and Snowflake. A September 2025 pricing overhaul replaced a single credit system with two meters — Actions and Vendor Credits — across a Free plan (200 Actions/month), Pro ($29/month), Team ($349/month) and a custom Enterprise tier. Notable customers include Canva, KPMG, Databricks, Autodesk, Confluent and Freshworks.

Relevance AI review →Relevance AI alternatives →

Read the full Make review

Make (formerly Integromat) is a visual AI automation platform for building and managing automations and AI agents — visually with its drag-and-drop scenario builder, in code, or from a prompt. It sits between Zapier's simplicity and n8n's raw power: complex branching, routers, data manipulation and AI modules are all first-class, with 3,000+ pre-built app integrations covering everything from Slack to Salesforce. Beyond point-to-point automation, Make's AI Agents let teams orchestrate multi-step, AI-driven processes across their stack, with an execution log, custom variables and enterprise governance (SSO, SOC 2/3) available on higher tiers. Pricing runs on a monthly operations credit allowance rather than a flat per-zap fee, scaling from a real free tier through Core, Pro, Teams and a custom Enterprise plan.

Make review →Make alternatives →