When client added in PT Distinction, sync it to Anthropic (Claude).

When a new client is added in PT Distinction, pass client onboarding inputs to Anthropic (Claude) to generate custom workout plans.

Try:

See all PT Distinction + Claude 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.

PT Distinction Explore PT Distinction →

Triggers

New member signed up

Fires when a new member, client or user joins in PT Distinction.

Class booked

Fires when someone books a class or session in PT Distinction.

Entry logged

Fires when a workout, habit, journal entry or goal is logged in PT Distinction.

Actions

Create or update member

Creates or updates a member's profile in PT Distinction.

Book a class or session

Books a class or session for a client in PT Distinction.

Log an entry

Logs a workout, habit or data point in PT Distinction.

Claude Explore Claude →

Triggers

New result returned

Fires when Claude returns a completion, prediction or other result.

Model run failed

Fires when a request to Claude errors or times out.

Fine-tune job completed

Fires when a fine-tuning job in Claude finishes.

Actions

Generate a completion

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

Run a model on an input

Sends text, an image or other data to Claude and returns the model's output.

Classify or extract data

Uses Claude to classify or extract structured data from text or images.

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FAQ

Common questions

Can Knit build “When client added in PT Distinction, sync it to Anthropic (Claude).” between PT Distinction and Claude?

Yes — describe it in the box above and Knit's Integrations Agent researches PT Distinction and Claude'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.