IntegrationsAutomation

Automation Platforms

Connect Transient Intelligence to Make, Zapier, n8n, or Power Automate. All automation tools use the same /v1/answer endpoint — trigger → HTTP POST with question and input → parse citations from the response.

Scenario setup

1. Add an HTTP → Make a request module.
2. Set method to POST, URL to https://api.transientintelligence.com/api/models/v1/answer.
3. Add header: x-api-key: your_api_key.
4. Set body type to JSON (application/json).
5. Map question and input from upstream modules (e.g. Google Drive file content).
6. Use citations from the response in downstream modules.

JSON body

{

"question": {{1.question}},

"input": {{2.fileContent}},

"top_k": 5

}

Zap setup

1. Choose your trigger (e.g. new file in Dropbox, new row in Google Sheets).
2. Add a Webhooks by Zapier → POST action, or use a Code by Zapier step for more control.
3. Set URL to /v1/answer, add the x-api-key header.
4. Pass question and input as data fields.
5. Map citations from the response to your output step (Slack, email, Sheets, etc.).

Code by Zapier (JavaScript)

const res = await fetch("https://api.transientintelligence.com/api/models/v1/answer", {

method: "POST",

headers: { "x-api-key": process.env.TI_API_KEY, "Content-Type": "application/json" },

body: JSON.stringify({

question: inputData.question,

input: inputData.fileContent,

top_k: 5

})

});

const data = await res.json();

return { citations: data.citations, answer: data.answer?.summary };

Workflow setup

1. Add an HTTP Request node.
2. Method: POST, URL: https://api.transientintelligence.com/api/models/v1/answer.
3. Authentication: Generic Credential Type → Header Auth, name x-api-key.
4. Body: JSON with question and input mapped from upstream nodes.
5. Use a Set or IF node downstream to branch on empty citations.

HTTP Request body (n8n expression)

{

"question": "{{ $json.question }}",

"input": "{{ $json.fileContent }}",

"top_k": 5

}

Response schema

Every /v1/answer response has the same shape. Map these fields in your downstream modules.

Response — /v1/answer

{

"answer": {

"summary": "string — synthesised answer grounded in citations",

"confidence": "number — 0 to 1"

"citations": [

{

"quote": "string — verbatim passage from the document",

"locator": "string — page / section / line reference",

"relevance": "number — passage relevance score"

}

"run_id": "string — use to retrieve full results via /v1/runs/{id}/results"

}

An empty citations array means no supporting evidence was found — branch on this in your flow rather than passing the empty response downstream.

Common mistakes

Passing a file path instead of file content

The input field expects the document text, not a path string like /drive/file.pdf. Download and extract the text in an upstream module before passing it to TI.

Missing Content-Type header

Set Content-Type: application/json on every request. Without it, some platforms (Zapier Webhooks, Power Automate HTTP) default to form-encoded and the body will be rejected.

Not branching on empty citations

If citations is empty, the model found no evidence — don't pass answer.summary downstream as if it were grounded. Add an IF/Condition node to handle the no-evidence path explicitly.

Sending binary file bytes as input

input must be plain text. For PDFs and DOCX files, use a text-extraction module (e.g. PDF.co, Adobe Extract, or Google Drive export as text/plain) before calling TI.