Automatically classify open-ended survey feedback

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

Try:

See all Wispform + VLM Run integrations or talk to a human

Trusted by teams already building on Knit·

4.9/5 on G2·

Google for Startups Accelerator

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.

VLM Run Explore VLM Run →

Triggers

New completion generated

Fires when VLM Run generates a response to a prompt.

Model run failed

Fires when a request to VLM Run errors or times out.

Fine-tune job completed

Fires when a fine-tuning job in VLM Run finishes.

Actions

Generate a completion

Sends a prompt to VLM Run and returns the model's response.

Summarize text

Uses VLM Run to summarize a block of text.

Classify or extract data

Uses VLM Run 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 VLM Run 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 VLM Run, automatically create an updated survey in Wispform to gather fresh test data from respondents. See details

See all Wispform + VLM Run integrations → · Browse the full workflow library →

Enterprise-grade security

Visit our Security Center Review the DPA

FAQ

Common questions

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

Yes — describe it in the box above and Knit's Integrations Agent researches Wispform and VLM Run'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 VLM Run improve how we process survey data from Wispform?

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

Can generated AI insights in VLM Run be saved back into Wispform?

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