Automatically classify open-ended survey feedback

When a user completes a survey in Wispform, send the feedback text to Token Metrics to automatically extract themes and classify respondent sentiments.

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See all Wispform + Token Metrics integrations or talk to a human

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How Knit builds this workflow

The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.

Wispform Explore Wispform →

Triggers

New form response

Fires when a form is submitted in Wispform.

Survey completed

Fires when a respondent finishes a survey in Wispform.

Response updated

Fires when an existing response is edited in Wispform.

Actions

Create or update form

Creates or updates a form or survey in Wispform.

Retrieve a response

Looks up a specific form response in Wispform.

Add a respondent

Adds a respondent or contact to a form in Wispform.

Token Metrics Explore Token Metrics →

Triggers

New completion generated

Fires when Token Metrics generates a response to a prompt.

Model run failed

Fires when a request to Token Metrics errors or times out.

Fine-tune job completed

Fires when a fine-tuning job in Token Metrics finishes.

Actions

Generate a completion

Sends a prompt to Token Metrics and returns the model's response.

Summarize text

Uses Token Metrics to summarize a block of text.

Classify or extract data

Uses Token Metrics to classify or extract structured data from text.

Summarize long form responses for quick review When a detailed form response is received in Wispform, use Token Metrics to generate a concise summary so your team can quickly digest key feedback. See details

Generate custom follow-up forms when model fine-tuning completes When a fine-tune job finishes in Token Metrics, automatically create an updated survey in Wispform to gather fresh test data from respondents. See details

See all Wispform + Token Metrics integrations → · Browse the full workflow library →

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FAQ

Common questions

Can Knit build “Automatically classify open-ended survey feedback” between Wispform and Token Metrics?

Yes — describe it in the box above and Knit's Integrations Agent researches Wispform and Token Metrics's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.

How long does it take to build?

Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.

How does Token Metrics improve how we process survey data from Wispform?

When customers complete surveys in Wispform, Token Metrics can instantly summarize long responses, extract key themes, or categorize customer feedback without manual reading.

Can generated AI insights in Token Metrics be saved back into Wispform?

Yes, after Token Metrics analyzes or summarizes response text, the resulting completion can be saved directly back into Wispform to enrich the response record.