# General Input vs. Make

> Compare General Input and Make for workflow automation. AI-native building and self-hosting vs. visual scenario builder with 3,000+ apps.

Make is the visual automation tool for power users. Its scenario builder uses a canvas where you drag modules, draw connections, and configure routers, iterators, and error handlers. It connects to 3,000+ apps and gives you granular control over every data transformation. For teams that want to see and manipulate every step of a complex data flow, Make's canvas is one of the most expressive tools available.

The visual power comes with a visual cost. Building a scenario means understanding modules, data mapping, filters, and Make's specific execution model. Your marketing manager isn't going to open the canvas and build a competitor monitoring workflow. And while Make has added AI agent modules, the platform's architecture is built around deterministic data routing, not AI-native execution where the model reasons across steps and tools.

## How they compare

<ComparisonTable
  competitor="Make"
  rows={[
    {
      feature: 'Natural language workflow building',
      gi: 'yes',
      competitor: 'partial',
    },
    { feature: 'Visual drag-and-drop builder', gi: 'no', competitor: 'yes' },
    { feature: 'App integrations', gi: 'partial', competitor: 'yes' },
    { feature: 'Built for non-technical users', gi: 'yes', competitor: 'no' },
    {
      feature: 'Execution monitoring with full history',
      gi: 'yes',
      competitor: 'yes',
    },
    { feature: 'Per-execution cost transparency', gi: 'yes', competitor: 'no' },
    {
      feature: 'Team workspaces with fine-grained permissions',
      gi: 'yes',
      competitor: 'partial',
    },
    {
      feature: 'Apps + deterministic scripts + AI agents',
      gi: 'yes',
      competitor: 'partial',
    },
    {
      feature: 'Choose any LLM (OpenAI, Anthropic, open source)',
      gi: 'yes',
      competitor: 'partial',
    },
    {
      feature: 'Human-in-the-loop approvals',
      gi: 'yes',
      competitor: 'partial',
    },
    {
      feature: 'Credential encryption isolated from AI',
      gi: 'yes',
      competitor: 'partial',
    },
    {
      feature: 'Self-hosted / on-prem deployment',
      gi: 'yes',
      competitor: 'no',
    },
  ]}
/>

## When to use Make

Make is the right choice for technically-minded operations teams that want a visual canvas to orchestrate complex multi-step data flows. If your automations involve heavy branching, iteration over arrays, and error handling across dozens of app modules, Make's scenario builder gives you control that text-based tools can't match. Its 3,000+ integration catalog is also hard to beat for breadth.

## When to use General Input

General Input is for teams that want production automation without the scenario-building learning curve.

- **Build by describing, not diagramming.** "When a deal closes in HubSpot, enrich the company with Apollo, draft an onboarding email, and wait for the account manager to approve." That's a working workflow in under a minute. In Make, it's 8+ modules to configure.
- **Non-technical users ship workflows.** Make requires understanding modules, data structures, and execution order. General Input lets ops, finance, and support teams build their own automations from plain English.
- **Three workflow types, one monitoring dashboard.** App integrations, deterministic code scripts, and AI agents all deploy and report in the same place. Make separates scenarios and agents, and doesn't offer standalone code workflows.
- **Cost per run, not credits per module.** Make bills by "operations" consumed across modules, making it hard to predict what a scenario will cost. General Input shows the dollar cost of every execution, broken down by step.
- **Self-hosted for compliance.** Credentials encrypted and isolated from AI context. Full on-prem deployment for regulated industries. Make is cloud-only.

## Better together

Make's visual canvas shines for complex data routing and transformation across its deep catalog. General Input handles the AI-native workflows where speed of building, team access, and cost visibility matter more than visual orchestration.