Melaya vs Make
Make is a mature visual automation platform with 3,000+ app integrations; Melaya is an AI agent builder that adds Android Device Control, approval gates, and cloud or local model execution.
Pick Make if your work is connecting well-known SaaS apps through visual, API-based scenarios at low cost: its 3,000+ integrations, mature branching tools, and $9 entry price beat Melaya on classic automation. Pick Melaya if you need AI agents with guardrails: human approval on every consequential write, per-step routing across 23 cloud and local model providers, deterministic evaluation with cost per accepted result, and Device Control that operates real Android apps with no API. Many teams keep Make for API plumbing and add Melaya where judgment, privacy, or a phone is involved.
Melaya vs Make, feature by feature
| Capability | Melaya | Make |
|---|---|---|
| Platform focus | Visual AI agent builder: agents, tools, triggers, and approval gates composed on a canvas | Visual automation platform: scenarios connecting apps, now extended with Make AI Agents |
| Mobile app control | Android Device Control: agents open allowed apps, read the screen, tap, type, and swipe on a real phone, guided by app playbooks, no API required | None. Apps are reached through their APIs; the Make mobile app is for running and monitoring scenarios |
| Human-in-the-loop | Approval gates are a built-in primitive on every consequential write, including an on-device approval before an agent publishes from a phone | No dedicated approval-gate primitive; approval flows are assembled manually from webhooks, email, or Slack modules |
| AI agents | Core product: 111 agent personas, multi-step agents with RAG and memory | Make AI Agents available across plans; as of 2026 they can call MCP tools and native modules in one reasoning loop |
| Model choice | Per-step model routing across 23 AI providers, cloud or local, bring your own model | Make's AI provider or your own LLM key; native OpenAI, Claude, and Gemini modules; cloud models |
| Local and self-hosted execution | Runs in the cloud or fully local via a local runner, including private on-prem inference | Cloud SaaS only; no self-hosted deployment as of 2026 |
| Evaluation and observability | Deterministic rule checks before any LLM judge, run traces, cost per accepted result | Execution history and logs; full-text log search on Pro and above; no built-in evaluation framework |
| Connector breadth | About 1,697 tools | 3,000+ pre-built app integrations, one of the largest catalogs in automation |
| Workflow logic | Canvas composition of agents, tools, triggers, and gates | Mature routers, iterators, aggregators, and error handlers for complex branching and data transformation |
| Pricing | Sandbox free, Outpost $20/mo with your own cloud keys, Forge for scheduled managed cloud; free open beta | Free 1,000 credits/mo; Core $9, Pro $16, Teams $29 per month; credit-based billing where module and agent actions consume credits |
| Compliance and maturity | Newer platform, currently in free open beta | SOC 2 Type II and GDPR, SSO on Enterprise, large template library and community; part of Celonis |
| Best for | Teams that need AI agents on real mobile apps, approval-gated writes, or local and private model execution | Ops teams automating API-connected SaaS apps at low cost with visual scenarios |
Where Melaya wins
- Device Control on Android: Melaya agents operate real apps on a real phone by reading the screen and tapping, typing, and swiping, with an on-device approval gate before anything publishes. Make can only reach apps that expose an API or webhook.
- Human-in-the-loop as a first-class primitive: every consequential write can require approval on the canvas, instead of hand-building approval loops from webhooks and email modules.
- Model freedom: per-step routing across 23 providers, including local models through a local runner, so sensitive workloads can run fully on your own hardware. Make agents run on cloud LLMs.
- Evaluation you can audit: deterministic rule checks run before any LLM judge, and every run exposes traces and cost per accepted result, not just execution logs.
- Predictable AI spend: Outpost is a flat $20/mo with your own cloud keys, so model usage is billed at provider cost rather than metered in platform credits.
Where Make wins
- Connector breadth and maturity: Make's 3,000+ pre-built integrations far exceed Melaya's roughly 1,697 tools, and its modules are battle-tested across years of production scenarios.
- Cheaper entry for classic automation: Core at $9/mo with 10,000 credits is hard to beat for high-volume, API-based workflows, and a free tier covers light use.
- Stronger deterministic workflow tooling: routers, iterators, aggregators, and error handlers make Make the better choice for complex data transformation between SaaS apps.
- Enterprise readiness: SOC 2 Type II, GDPR, Enterprise SSO, and a large template library and community that a platform in open beta cannot yet match.
Melaya vs Make: frequently asked questions
Is Melaya a good Make alternative?
Melaya is a good Make alternative when the job is AI agents rather than API plumbing: it adds approval gates on every consequential write, per-step routing across 23 cloud and local model providers, deterministic evaluation, and Android Device Control for apps with no API. If your automations are mostly connecting SaaS apps through their APIs, Make's 3,000+ integrations and lower entry price make it the better fit. Many teams run both.
Can Melaya do what Make does?
Partly. Melaya covers triggers, roughly 1,697 tools, and multi-step logic on a visual canvas, so many scenario-style automations translate directly. Make is still stronger for heavy data transformation between SaaS apps, with mature routers, iterators, and aggregators and a much larger integration catalog.
How much does Melaya cost compared to Make?
Melaya has a free Sandbox, Outpost at $20/mo where you bring your own cloud keys, and Forge for scheduled managed cloud runs; it is currently in free open beta. Make starts free with 1,000 credits per month, then Core $9, Pro $16, and Teams $29 per month, with module and agent actions consuming credits. Make is cheaper to start; Melaya's flat plan avoids per-action metering on AI-heavy workloads because model usage is billed by your provider at cost.
Can Make control mobile apps the way Melaya does?
No. Make integrates apps through their APIs and webhooks, and its mobile app is for running and monitoring scenarios. Melaya's Device Control runs agents on a real Android phone: they open allowed apps, read the screen, tap, type, and swipe, with an on-device approval gate before anything is published, so apps without an API are still automatable.
Does Make have AI agents?
Yes. Make AI Agents shipped in 2026 and are available across plans, using Make's AI provider or your own LLM key, and as of mid-2026 they can call MCP tools and native modules in the same reasoning loop. The differences are guardrails and deployment: Melaya adds built-in approval gates, deterministic-first evaluation with cost per accepted result, and the option to run agents fully locally.
Can I run Melaya or Make with local AI models?
Melaya yes: a local runner lets you route any step to local models and even run the whole platform on your own hardware for private inference. Make is cloud SaaS only as of 2026; you can bring your own LLM key, but agents execute against cloud model providers and there is no self-hosted deployment.
Which is better for AI-heavy workflows, Melaya or Make?
Melaya, in most cases. It routes each step to the best of 23 providers, checks outputs with deterministic rules before any LLM judge, shows cost per accepted result, and gates consequential writes behind human approval. Make's agents are capable and improving, but evaluation, model choice, and approvals are thinner, and agent actions consume plan credits.
Do I have to choose between Melaya and Make?
No. A common setup keeps Make for high-volume, deterministic API automations where its credit pricing is cheapest, and uses Melaya for the work Make cannot do: agents that need approval gates, local or private models, measurable evaluation, or hands on a real Android phone. Both platforms have free tiers, so trying the split costs nothing.
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