Make and Zapier

Make and Zapier don't need a dedicated app to use FluentC. Both can send an HTTP request, and that is all the REST API needs.

The request

Every step uses the same settings:

Body for real-time mode:

{
  "input": "{{your text from the previous step}}",
  "input_format": "text",
  "target_language": "es",
  "mode": "real-time"
}

Map your own text into input with the tool's field picker. The {{ }} above stands for that mapping. The response has the translation in translation. See Translate for every field and Authentication for the key.

Note: Real-time mode needs the Real-time plan. On a Batch plan key use "mode": "batch" and the polling pattern below.

Make

1. Add the HTTP → Make a request module.
2. Set URL, Method (POST) and the two Headers from the table.
3. Set Body type to Raw, Content type to JSON (application/json), and paste the body into Request content.
4. Turn on Parse response. The fields translation, status and source_language_detected are then available to later modules.
5. If a request can fail, add an error handler route so one bad item doesn't stop the scenario.

Zapier

1. Add an action: Webhooks by Zapier → Custom Request.
2. Set Method to POST and URL to the translate URL.
3. In Data, paste the JSON body and map your fields into it.
4. In Headers, add Authorization and Content-Type as pairs.
5. Later steps can use translation from the response.

Example: translate form submissions

1. Trigger: a Google Form response is submitted.
2. Request: translate the answer into your team's language (real-time).
3. Deliver: add the translation to a Google Sheet row, or post it to Slack.

The same shape works for CRM records, support tickets and chat messages.

Batch with polling

Use batch for large or scheduled work, or when your key is on the Batch plan. It takes two requests.

1. Submit. The same request with "mode": "batch". The response is { "job_id": "..." }.

2. Wait, then fetch. Add a delay (10 seconds is a good start), then send:

The response status is processing, complete or failed. Branch on it with a filter or a router: if complete, use translation; if processing, wait and repeat; if failed, handle the error. Cap the repeats, because an unknown job_id also reports processing. See Batch results.

Tip: If you'd rather not build the polling loop, n8n does it for you. See the n8n node.

Avoiding duplicate work

FluentC answers repeated text from translation memory, so sending the same string twice is cheap. Plan limits still count the calls: the Batch plan allows 20 calls per hour. Send several strings in one batch request instead of one request per string, where your content allows it.

Troubleshooting

More in Errors.