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Make alternative

A Make alternative, for when a scenario needs guardrails.

Teams usually leave Make for a reason other than the builder. The need is governance the scenario cannot bypass: model spend that stops at a limit, a step a person must approve, one installation serving many customers. Here is how OCNORA meets each need, what the move involves, and when Make remains the better fit.

Book a technical demoThe full comparison

Every Make figure on this page is quoted from a page Make publishes, with the date we read it, and is the same figure the full comparison prints. Every OCNORA statement shows its evidence level and the date it was checked. We do not state what Make lacks.

Who is looking

Who searches for a Make alternative.

  • Teams running AI agents in production who need spend capped before the call, not reported after it.
  • Operations teams where a person signs off a step before it writes anywhere.
  • Engineering teams who want a Python code step in their workflows.
  • Software companies embedding automation for their own customers, one tenant each.
Why, and how OCNORA answers

The reasons, one by one.

Each reason is a need, not a verdict on Make. Where Make publishes something relevant, it is quoted with its source.

  1. Billing that counts whole workflows

    You want cost to follow workflow executions and AI spend.

    Billing unit, as Make publishes it
    Credits per monthmake.com/en/pricing · 2026-09-22

    A Make credit and an OCNORA execution are not the same unit.

    How OCNORA answers it

    Every deployment is quoted; usage is counted in full workflow executions plus AI spend. There is no free tier and no public price list.

    Evidence: unverified · checked 2026-09-28

  2. AI agents under a budget

    Agent spend has to be held at a limit per workspace, provider or tenant.

    AI agents stated by the vendor, as Make publishes it
    Make AI Agentsmake.com/en/ai-agents · 2026-09-22

    OCNORA: a provider-neutral agent node inside the workflow graph, under per-tenant token and USD budgets.

    How OCNORA answers it

    Every model call is written to a ledger with its tokens and USD cost. Monthly token and USD budgets per workspace and per provider (on Embedded, per tenant) are checked before a call from an estimate and reconciled after it; a circuit breaker holds further calls when a budget is used up or a provider keeps failing.

    Evidence: unverified · checked 2026-09-28

  3. A code step in Python

    Your team writes Python and wants a code step in any workflow.

    Code step, as Make publishes it
    Custom functions in JavaScript, Enterprise onlyhelp.make.com/custom-functions · 2026-09-22
    How OCNORA answers it

    The code node runs Python and is offered on every deployment.

    Evidence: unverified · checked 2026-09-28

  4. A person must approve some steps

    A write waits for a named approver, with a timeout and a recorded decision.

    How OCNORA answers it

    A human.prompt step suspends a run until a person answers or its timeout lapses, then routes on the answer or on the timeout branch. The decision is recorded with the run.

    Evidence: unverified · checked 2026-09-28

  5. One installation for many customers

    Your own product offers automation to its customers, each tenant isolated.

    How OCNORA answers it

    OCNORA runs on OCNORA Cloud, on the customer’s own cloud from the Docker Compose file or the Helm chart in the backend repository, or embedded in the customer’s product. The Helm chart runs each process role as its own deployment, including Workflow Health, Auto Fix and the task orchestrator.

    Evidence: unverified · checked 2026-09-28

Migration

Moving from Make.

There is no Make importer: each scenario is rebuilt in the builder, then checked before it runs.

  1. STEP 1

    List what runs in Make

    Start from the scenarios that run in production and the apps each one touches. OCNORA’s importer reads n8n workflow JSON only, so Make scenarios are rebuilt, not converted.

  2. STEP 2

    Find each app in the catalogue

    Look each app up in the integration catalogue. Some providers have no typed nodes and are reached with a credential and the HTTP node.

  3. STEP 3

    Rebuild from a template or with Build with AI

    Start from a published template, or describe the workflow and let Build with AI draft it, then fill in the connections. Visual builder, expressions, test step.

  4. STEP 4

    Check it before it runs

    Workflow Health validates each workflow and pre-flights its connections on save and publish. Auto Fix repairs one broken node at a time and re-checks; a code finding it cannot answer can go to a host runner as a draft pull request or an issue; every other finding is handed to a person. A dry run executes the workflow graph with side effects suppressed, so each step’s output shape can be read before the first real trigger.

  5. STEP 5

    Switch the trigger last

    Run both side by side until the run history matches, then point the trigger at OCNORA. Each run keeps its steps with their input, output, status and the connection used, and the audit log records who changed which workflow, connection or setting and when. The audit log is exportable.

Browse the integration catalogue and the templates before the demo.

Being fair

When to stay with Make.

We would rather you pick the right tool than pick us and regret it.

  • Procurement requires SOC 2 or ISO 27001

    Make states SOC 2 Type II, SOC 3 and an ISO 27001 certified information security program. OCNORA documents its controls and shares them under NDA.

  • You want a very cheap entry point

    Make publishes a $9/mo plan with 5,000 credits. If cost per operation is the deciding factor at small volume, Make is hard to beat.

  • Your team writes JavaScript, not Python

    Make’s custom functions are JavaScript. OCNORA’s code node is Python.

  • You need one deep app, not many governed ones

    Make’s per-app operation depth is excellent. If your automation lives inside a single SaaS tool, governance across tenants buys you little.

The full comparison, and where every Make figure came from

OCNORA vs Make puts everything both vendors publish side by side, with every source. The Make figures on this page came from:

  1. 1.make.com/en/pricing — read 2026-09-22
  2. 2.make.com/en/ai-agents — read 2026-09-22
  3. 3.help.make.com/custom-functions — read 2026-09-22

Something out of date? Tell us and we will fix it.

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