Make

Make is what mid-market ops teams reach for when Zapier stops scaling and self-hosted n8n is more infrastructure than they want to own. It's a visual workflow automation platform built around scenarios, modules, routers, and iterators, the building blocks you need for real branching logic, not just linear if-this-then-that chains.

What Make Does

Make connects your stack through visual scenarios that can branch, loop, retry, and call sub-scenarios. The architecture rewards teams that think in workflows rather than triggers. Every run is logged module-by-module, which makes debugging and iteration faster than any other hosted automation tool we work in.

• Scenarios: visual flows built from connected modules, each representing an action in an app or a logic step.
• Routers and filters: conditional branching that splits a scenario into parallel paths based on data, with per-path filters.
• Iterators and aggregators: loop through arrays of records and recombine results, which is the work most teams resort to scripts for.
• Error handlers: per-module retry, rollback, and fallback paths so a single bad record doesn't kill the run.
• Data stores and custom variables: lightweight built-in storage and reusable state, which removes the need for an external database in most ops scenarios.
• Webhooks and HTTP modules: bidirectional integration with anything that exposes an API, including bespoke internal systems.
• 3,000+ pre-built app integrations: including Salesforce, HubSpot, NetSuite, Slack, Stripe, Airtable, Notion, monday.com, Shopify, Google Workspace, and most of the long tail.

Make's AI Layer

Make has shipped a serious AI surface area over the last year. Make AI Agents let you build agents that take action across the 3,000+ connected apps with a transparent execution map, you can see every module the agent fires. The Make MCP Server exposes scenarios to AI clients, so Claude or ChatGPT can call your workflows as tools. Native modules for OpenAI, Anthropic Claude, Google Gemini, Perplexity, and ElevenLabs mean the prompt and the orchestration live in the same place, which is the version of AI automation we actually trust in production.

Automations We Build with Make

Make is the right tool for any ops workflow that has real branching, depends on multiple systems, and needs to be auditable. Below are the plays we run most often for mid-market clients, the ones that meaningfully change throughput rather than just save a few clicks.

• Inbound lead orchestration: form submission triggers enrichment via Clay or Apollo, scoring against an ICP rubric, router-based assignment to the right rep, and a personalised first-touch sequence in the CRM.
• Order-to-cash automation: new Stripe subscriptions trigger CRM updates, NetSuite or QuickBooks invoicing, customer welcome emails, and CSM assignment, with error handlers that route exceptions to a Slack channel.
• Client onboarding pipelines: a closed-won deal in HubSpot or Salesforce fires a master scenario that provisions accounts, sends document signing requests, creates project workspaces, and schedules kickoff calls.
• AI-assisted support triage: inbound tickets get classified by an LLM module, routed to the right queue, and pre-drafted with a suggested reply that an agent reviews instead of writing from scratch.
• Cross-stack data reconciliation: nightly scenarios that compare CRM, billing, and finance records, flag mismatches, and write a summary to the ops Slack channel before anyone logs in.
• Recruiting and hiring ops: applications from Greenhouse or Ashby trigger enrichment, AI-powered resume screening, calendar scheduling, and a structured intake message to the hiring manager.
• Reporting and digest scenarios: scheduled runs that pull from the warehouse, the CRM, and the finance stack, summarise via an LLM, and post weekly leadership digests to Slack or email.

Why Teams Choose Make

• Real branching logic: routers, iterators, and error handlers replace the dozen-Zap workarounds that mid-market ops teams accumulate on Zapier.
• Module-level execution logs: every run shows exactly which step ran on which data, which makes debugging and iteration roughly an order of magnitude faster than other hosted tools.
• Hosted infrastructure: SOC 2 Type II, GDPR-compliant, SSO available, with no servers to patch. The right answer for teams that want power without owning the ops.
• Operations-based pricing that scales linearly: predictable cost as volume grows, without per-Zap or per-seat ceilings that punish you for building more.
• 3,000+ native integrations and a clean HTTP module, if the app exists, Make either has it natively or you wire it in via webhooks in minutes.

Make integrates natively with the tools you already run, Salesforce, HubSpot, NetSuite, Slack, Stripe, Airtable, Notion, monday.com, Shopify, Google Workspace, and a long tail of 3,000+ apps. Plans start with a free tier and scale through Core, Pro, Teams, and Enterprise (pricing typically lands in the low double digits per month at the entry tiers, with Enterprise quoted custom). That's the layer Moonira builds on, you get the scenarios, the error handling, the AI orchestration, and the ongoing iteration without standing it up yourself.