chores: oct 28 changes (#466)

* add security section to sidebar

* remove references to lemur in integrations

Author: m-ods

fern/docs.yml

@@ -291,6 +291,24 @@ navigation:
                 path: pages/08-concepts/account_management.mdx
               - link: Security page
                 href: https://assembly.ai/trust
+          - section: Security
+            icon: lock
+            skip-slug: true
+            contents:
+              - link: Trust Center
+                href: https://www.assemblyai.com/security
+              - link: Do you train on customer data?
+                href: /docs/faq/are-files-submitted-to-the-api-used-for-model-training
+              - link: Does AssemblyAI use encryption?
+                href: /docs/faq/are-audio-and-text-files-encrypted
+              - link: Are you GDPR compliant?
+                href: /docs/faq/are-you-gdpr-compliant
+              - link: Are you HIPAA compliant?
+                href: /docs/faq/are-you-hipaa-compliant
+              - link: Do you have SOC2 certification?
+                href: /docs/faq/do-you-have-soc2-certification
+              - link: Does AssemblyAI offer zero data retention?
+                href: /docs/faq/does-assemblyai-offer-zero-data-retention
           - section: Integrations
             icon: duotone code-fork
             path: pages/06-integrations/index.mdx

fern/pages/06-integrations/activepieces.mdx

@@ -6,7 +6,7 @@ hide-nav-links: true
 
 [Activepieces](https://www.activepieces.com/) is an open-source, no-code automation platform that enables users to streamline workflows by connecting various applications and automating tasks.
 
-With the AssemblyAI piece for Activepieces, you can use AssemblyAI to transcribe audio data with speech recognition models, analyze the data with audio intelligence models, and build generative features on top of it with LLMs.
+With the AssemblyAI piece for Activepieces, you can use AssemblyAI to transcribe audio data with speech recognition models, analyze the data with speech understanding models, and build generative features on top of it with LLMs.
 You can supply audio to the AssemblyAI piece and connect the output of any of AssemblyAI's models to other services in your Activepieces flow.
 
 ## Quickstart
@@ -60,7 +60,7 @@ If you don't have a publicly accessible URL, you can use the Upload a File modul
 If you don't want to wait until the transcript is ready, uncheck the `Wait until transcript is ready` parameter.
 
 <Info>
-  Configure your desired [Audio Intelligence models](/audio-intelligence) when
+  Configure your desired [Speech Understanding models](/speech-understanding) when
   you create the transcript. The results of the models will be included in the
   transcript output.
 </Info>
@@ -119,21 +119,6 @@ Deleting a transcript doesn't delete the transcript resource itself, but removes
   "error".
 </Note>
 
-### LeMUR
-
-#### Run a Task using LeMUR
-
-Prompt different LLMs over your audio data using LeMUR.
-You have to configure either the `Transcript IDs` or `Input Text` input field.
-
-#### Retrieve LeMUR response
-
-Retrieve a LeMUR response that was previously generated.
-
-#### Purge LeMUR request data
-
-Delete the data for a previously submitted LeMUR request.
-Response data from the LLM, as well as any context provided in the original request will be removed.
 
 ### Other actions
 

fern/pages/06-integrations/make.mdx

@@ -6,7 +6,7 @@ hide-nav-links: true
 
 [Make](https://make.com/) (formerly Integromat) is a workflow automation tool that lets you integrate various services together without requiring coding knowledge.
 
-With the AssemblyAI app for Make, you can use our AI models to process audio data by transcribing it with speech recognition models, analyzing it with audio intelligence models, and building generative features on top of it with LLMs.
+With the AssemblyAI app for Make, you can use our AI models to process audio data by transcribing it with speech recognition models, analyzing it with speech understanding models, and building generative features on top of it with LLMs.
 You can supply audio to the AssemblyAI app and connect the output of our models to other services in your Make scenarios.
 
 ## Quickstart
@@ -70,7 +70,7 @@ If you don't have a publicly accessible URL, you can use the [Upload a File](#up
 If you don't want to wait until the transcript is ready, change the `Wait until Transcript is Ready` parameter to `No` under **Show advanced settings**.
 
 <Info>
-  Configure your desired [Audio Intelligence models](/audio-intelligence) when
+  Configure your desired [Speech Understanding models](/speech-understanding) when
   you create the transcript. The results of the models will be included in the
   transcript output.
 </Info>
@@ -140,17 +140,6 @@ Deleting a transcript does not delete the transcript resource itself, but remove
   "error".
 </Note>
 
-### LeMUR
-
-#### Run a Task using LeMUR
-
-Prompt different LLMs over your audio data using LeMUR.
-You have to configure either the `Transcript IDs` or `Input Text` input field.
-
-#### Purge a LeMUR Request
-
-Delete the data for a previously submitted LeMUR request.
-Response data from the LLM, as well as any context provided in the original request will be removed.
 
 ### Other modules
 

fern/pages/06-integrations/postman.mdx

@@ -94,23 +94,6 @@ Now that you have a completed transcript, you can send these other HTTP requests
   - Get paragraphs in transcript
   - Search words in transcript
   - Get redacted audio (if PII audio redaction is enabled)
-- LeMUR
-  - Run a task using LeMUR
-  - Summarize a transcript using LeMUR
-  - Ask questions using LeMUR
-  - Extract action items
-
-Let's prompt an LLM to summarize the transcript using LeMUR:
-
-1. Open the **LeMUR > Run a task using LeMUR** request
-2. Switch to the **Body** tab
-3. Find the `transcript_ids` property and replace the sample ID with your transcript ID
-4. Set the `final_model` property to ` "anthropic/claude-3-5-sonnet"`
-5. Set the `prompt` property to `"Summarize the transcript"`
-6. Remove the other properties
-7. Click the **Send** button
-
-![Summarize transcript using LeMUR](../../assets/img/integrations/postman/8-lemur.png)
 
 </Step>
 </Steps>

fern/pages/06-integrations/power-automate.mdx

@@ -7,7 +7,7 @@ hide-nav-links: true
 [Microsoft Power Automate](https://www.microsoft.com/en-us/power-platform/products/power-automate) is a low-code workflow automation platform with a rich collection of connectors to Microsoft's first-party services and third-party services. [Azure Logic Apps](https://learn.microsoft.com/en-us/azure/logic-apps/logic-apps-overview) is the equivalent service built for developers and IT pros.
 
 The AssemblyAI connector makes our API available to both Microsoft Power Automate and Azure Logic Apps.
-With the connector, you can use AssemblyAI to transcribe audio data with speech recognition models, analyze the data with audio intelligence models, and build generative features on top of it with LLMs.
+With the connector, you can use AssemblyAI to transcribe audio data with speech recognition models, analyze the data with speech understanding models, and build generative features on top of it with LLMs.
 You can supply audio to the AssemblyAI connector and connect the output of our models to other services in your flows.
 
 ## Quickstart
@@ -49,7 +49,7 @@ Once you transcribe the file, the file will be removed from AssemblyAI's servers
 ## Transcribe Audio
 
 To transcribe your audio, configure the `Audio URL` parameter using your audio file URL.
-Then, configure the additional parameters to enable more [Speech Recognition](https://www.assemblyai.com/docs/speech-to-text/pre-recorded-audio) features and [Audio Intelligence](https://www.assemblyai.com/docs/audio-intelligence) models.
+Then, configure the additional parameters to enable more [Speech Recognition](https://www.assemblyai.com/docs/speech-to-text/pre-recorded-audio) features and [Speech Understanding](https://www.assemblyai.com/docs/speech-understanding) models.
 
 The result of the Transcribe Audio action is a queued transcript which will start being processed immediately.
 To get the completed transcript, you have two options:
@@ -216,7 +216,7 @@ The output of this action is a `queued` transcript. Learn [how to wait until the
 </Warning>
 
 <Info>
-  Configure your desired [Audio Intelligence models](/audio-intelligence) when
+  Configure your desired [Speech Understanding models](/speech-understanding) when
   you create the transcript. The results of the models will be included in the
   transcript output when the transcript is completed.
 </Info>
@@ -274,20 +274,6 @@ Delete the transcript. Deleting does not delete the resource itself, but removes
   `error`.
 </Note>
 
-### LeMUR
-
-#### Run a Task Using LeMUR
-
-Use the LeMUR task endpoint to input your own LLM prompt.
-You have to configure either the `Transcript IDs` or `Input Text` input field.
-
-#### Retrieve LeMUR Response
-
-Retrieve a LeMUR response that was previously generated.
-
-#### Purge LeMUR Request Data
-
-Delete the data for a previously submitted LeMUR request. The LLM response data, as well as any context provided in the original request will be removed.
 
 ## Additional resources
 

fern/pages/06-integrations/rivet.mdx

@@ -6,7 +6,7 @@ hide-nav-links: true
 ---
 
 [Rivet](https://rivet.ironcladapp.com/) is an open-source visual AI programming environment.
-Through a collaboration between AssemblyAI and Rivet, you can use AssemblyAI speech-to-text and LeMUR capabilities in Rivet.
+Through a collaboration between AssemblyAI and Rivet, you can use AssemblyAI speech-to-text capabilities in Rivet.
 
 ## Quickstart
 
@@ -40,35 +40,6 @@ The Transcribe Audio node transcribes audio using the [AssemblyAI API](https://w
 
 ![Transcribe Audio node](../../assets/img/integrations/rivet/transcribe-audio-node.png)
 
-### LeMUR nodes
-
-LeMUR is a framework by AssemblyAI to process audio files with an LLM.
-The AssemblyAI plugin has a dedicated node for each LeMUR endpoint.
-Each node accepts Transcript IDs or Input Text as input which you can get from the Transcribe Audio node. Additional parameters are available as inputs and as node configuration. For more information what these parameters do, see [LeMUR API reference](https://www.assemblyai.com/docs/api-reference/lemur).
-
-#### LeMUR Summary node
-
-The LeMUR Summary node uses LeMUR to summarize a given transcript.
-
-![LeMUR Summary node](../../assets/img/integrations/rivet/lemur-summary-node.png)
-
-#### LeMUR Q&A node
-
-LeMUR can generate answers from a transcript and questions.
-
-![LeMUR Question & Answer node](../../assets/img/integrations/rivet/lemur-qna-node.png)
-
-#### LeMUR Custom Task node
-
-LeMUR can generate a response from a prompt and transcript.
-
-![LeMUR Custom Task node](../../assets/img/integrations/rivet/lemur-task-node.png)
-
-#### LeMUR Action Items node
-
-The LeMUR Action Items node returns a list of action items from a meeting transcript.
-
-![LeMUR Action Items node](../../assets/img/integrations/rivet/lemur-action-items-node.png)
 
 ## Additional resources
 

fern/pages/06-integrations/twilio.mdx

@@ -6,7 +6,7 @@ hide-nav-links: true
 
 Twilio is a programmable communication platform for voice, messaging, and email.
 By combining Twilio with AssemblyAI, you can transcribe voice calls in [real-time](/docs/speech-to-text/streaming), and voice recordings and voice messages [asynchronously](/docs/speech-to-text/pre-recorded-audio).
-Combine transcription with our [audio intelligence models](/docs/audio-intelligence/summarization) and [LeMUR LLM framework](/docs/lemur/summarize-audio) to analyze the calls and messages.
+Combine transcription with our [speech understanding models](/docs/speech-understanding/summarization) to analyze the calls and messages.
 
 Blog posts:
 

fern/pages/06-integrations/zapier.mdx

@@ -5,7 +5,7 @@ hide-nav-links: true
 ---
 
 Zapier is a workflow automation tool that lets you integrate various services together without requiring coding knowledge.
-You can use our AI models to process audio data by transcribing it with speech recognition models and analyzing it with audio intelligence models.
+You can use our AI models to process audio data by transcribing it with speech recognition models and analyzing it with speech understanding models.
 You can supply audio to the AssemblyAI app and connect the output of our models to other services in your Zaps.
 
 ## Quickstart
@@ -97,10 +97,6 @@ Get the result of the redacted audio model.
 
 <Note>You can only invoke this action after the transcript is completed.</Note>
 
-### What about LeMUR?
-
-Unfortunately, the Zapier platform doesn't have the necessary features for us to reliably offer LeMUR, our LLM framework for speech understanding.
-We're looking at different avenues to add support in the future, but we have no timeline for when LeMUR support will be available.
 
 ## Testing with sample data