Make (AI Agents) extends Make's visual no-code automation platform with AI agents that can make decisions and take multi-step actions inside a workflow, aimed at operations, marketing and IT teams who already build or want to build automations across thousands of connected apps rather than developers wanting a code-first framework.
Who it's for
Make suits teams that need both classic, deterministic automation (if this happens, do that) and AI-driven decision-making layered on top — for example, an agent that reads an inbound request, decides which of several workflows applies, and only then triggers the right one. It's popular with agencies, marketing operations and IT teams managing many interconnected tools, and its generous free tier and low entry price make it accessible to freelancers and small businesses, not just enterprises.
How it works
Workflows (called "scenarios") are built on a visual canvas by connecting modules for different apps and logic steps; AI agents can be embedded into these scenarios to interpret unstructured input, choose a path semi-autonomously, or generate content as part of a larger automated process. Make supports choosing among multiple underlying AI models rather than being locked to one, and an API is available for teams that want to trigger or extend scenarios programmatically. Because Make bills on an operations/credits basis, cost scales with how many steps a scenario executes rather than with a flat per-agent fee.
Pricing
Make has a free tier for getting started, and paid plans begin at roughly $9 per month, billed on a credit-based ("operations") model where cost scales with usage. Complex scenarios with many steps or AI calls consume more credits than simple ones, so check Make's current pricing page to estimate cost for your expected volume.
Strengths and trade-offs
Make's core strength is breadth combined with visual clarity: it connects to roughly 3,000 apps, has a genuinely no-code builder that's still expressive enough for complex branching logic, offers audit logging for oversight, and now layers AI agents on top of that same automation engine rather than requiring a separate tool. The trade-offs are that credit-based pricing can be harder to predict than flat billing for high-volume users, and there's no documented self-hosted option, so it's cloud-only. For teams that want both reliable, rule-based automation and AI judgment in the same platform, Make (AI Agents) is one of the strongest, most affordable options available. A practical example is an agent that reads an inbound support ticket, classifies its urgency and topic, and then routes it into the right one of several pre-built scenarios — combining AI judgment with the deterministic reliability Make's automation engine has been known for since its Integromat days.