Connect Speechnotes and metatext to Build Intelligent Automations

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Speechnotes

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Choose an Action

metatext

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Enable Integrations or automations with these events of Speechnotes and metatext

Enable Integrations or automations with these events of Speechnotes and metatext

Actions

Transcribe Audio

Transcribe Audio

Convert an audio or video file into a text transcript. Supports language selection, speaker count, and optional partial-range transcription.

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Frequently Asked Questions

How do I start an integration between Speechnotes and metatext?

To start, connect both your Speechnotes and metatext accounts to viaSocket. Once connected, you can set up a workflow where an event in Speechnotes triggers actions in metatext (or vice versa).

Can we customize how data from Speechnotes is recorded in metatext?

Absolutely. You can customize how Speechnotes data is recorded in metatext. This includes choosing which data fields go into which fields of metatext, setting up custom formats, and filtering out unwanted information.

How often does the data sync between Speechnotes and metatext?

The data sync between Speechnotes and metatext typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from Speechnotes to metatext?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Speechnotes and metatext?

Yes, you can set conditional logic to control the flow of data between Speechnotes and metatext. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.

Speechnotes

About Speechnotes

Automatically transform all audio recordings to text. Most accurate AI transcription (speech to text) engines. Fast, affordable, secure & private.

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metatext

About metatext

Metatext is a easy to use AI tool to create and manage robust language models for classification, extraction and generation tasks.

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