What are these tools?
- Zapier is a cloud automation service: "when this happens in app A, do that in app B". It has a very large library of app connectors and is the easiest to start with.
- Make (formerly Integromat) is a cloud automation service with a visual scenario builder. It's good at multi-step flows with branching and data transformation.
- n8n is a workflow automation tool you can self-host on your own server or use as a cloud service. It's popular with technical teams for its flexibility, code nodes and data control.
- A custom AI agent is software (often built with one of the tools above, or in code) that uses a language model to understand messy input and decide which predefined tools to call, within a stop rule.
How do they compare?
| Zapier | Make | n8n | Custom agent | |
|---|---|---|---|---|
| Hosting | Cloud | Cloud | Self-host or cloud | Your choice |
| Ease of start | Easiest | Easy to moderate | Moderate (technical) | Needs a builder |
| Cost model | Per task, by plan | Per operation, by plan | Server cost if self-hosted, or a cloud plan | Build plus AI usage plus hosting |
| Handles messy free text | Via AI steps | Via AI steps | Via AI nodes | Core strength |
| Data control | Vendor cloud | Vendor cloud | Can stay on your server | Designed per case |
Check each vendor's site for current plans and limits; they change often.
When is Zapier the right choice?
Simple, low-volume connections between popular SaaS apps, when nobody technical is available. Example: a new Typeform response creates a HubSpot contact and posts to Slack.
When is Make the right choice?
Multi-step flows with branching, loops and data reshaping, where you still want a visual cloud tool. It often costs less than Zapier for the same complex flows, but compare current plans.
When is n8n the right choice?
When volumes are high and per-task pricing gets expensive; when data should stay on infrastructure you control (relevant for DPDP and sensitive data); or when you need custom code steps. It needs someone to host, update and monitor it.
When do you need a custom AI agent?
When the input is unstructured (WhatsApp messages, emails, PDFs) and the workflow needs to understand intent, pick the right action and draft a response, with approval for risky steps. The agent usually sits on top of one of the tools above, which handles the reliable plumbing.
How do you decide quickly?
- Structured data between popular apps, low volume: Zapier.
- Complex structured flows, cloud: Make.
- High volume, data control or custom code: n8n.
- Messy human input plus decisions: a custom agent with a stop rule, on top of one of the above.
How do we apply this in client work?
Everything on this page feeds into how we run pilots. We start with a consultation to understand the process and the people involved, then write a one-page scope: the trigger, inputs, steps, outputs, a success measure and a stop rule that says what the agent may do alone, what needs approval and when it must hand over. We build inside the tools you already use, test on real or realistic cases including awkward ones, and review the results with your team before anyone talks about expanding.
We keep a few habits on every project: we never publish invented results, we label examples as illustrations, we list third-party costs separately, and we say so plainly when something isn't worth automating yet. If that sounds like the kind of partner you want, read the pilot process or message us on WhatsApp.
What should you prepare before talking to us?
You don't need a technical brief. A useful first conversation needs only a few things, and gathering them is valuable even if you never work with us:
- The process in plain words: what triggers it, who does what, and where it usually goes wrong.
- Rough volumes: how many messages, orders, tickets or invoices per week. A one-week tally is enough.
- Your tools: WhatsApp app or API, CRM, sheets, accounting or helpdesk software, including versions or plans where you know them.
- Three real examples: typical messages or cases, plus one awkward one, with personal details removed.
- What must never happen: the mistakes that would hurt most. These become the first lines of your stop rule.
- An owner: the person who will review the workflow once it runs.
Send these on WhatsApp or by email, or run the pilot scorecard first.
How does a pilot with us work?
Every engagement follows the same four steps. Consult: you walk us through the process, the tools and where it breaks. Pick the pilot: we choose one workflow and write down its inputs, outputs, tools, stop rule and success measure. Ship: we build it into the tools you already use and test it on real cases. Review: your team checks what the agent did and what it escalated, then decides whether to tune it, expand it or stop. Read the full pilot process.