docs: add hidden self-hosted async transcription documentation

fern/docs.yml

@@ -287,6 +287,9 @@ navigation:
               - page: Self-hosted streaming
                 path: pages/05-guides/self-hosted-streaming.mdx
                 hidden: true
+              - page: Self-hosted async
+                path: pages/05-guides/self-hosted-async.mdx
+                hidden: true
               - page: Webhooks
                 path: pages/05-guides/webhooks.mdx
               - page: Evaluating STT models

fern/pages/05-guides/self-hosted-async.mdx

@@ -0,0 +1,198 @@
+---
+title: "Self-Hosted Async Transcription"
+hide-nav-links: true
+description: "Deploy AssemblyAI's async transcription solution within your own infrastructure"
+---
+
+The **AssemblyAI Self-Hosted Async Solution** provides a secure transcription solution that can be deployed within your own infrastructure. This solution is designed for partners who need complete control over their data and infrastructure while maintaining high-quality speech-to-text capabilities.
+
+## Core principle
+
+- **Complete data isolation**: No audio data, transcript data, or personally identifiable information (PII) will ever be sent to AssemblyAI servers. Only usage metadata and licensing information is transmitted.
+
+## System requirements
+
+### Hardware requirements
+
+- **GPU**: NVIDIA GPU support required (any NVIDIA GPU model will work)
+
+### Software requirements
+
+- **Operating System**: Linux
+- **Container Runtime**: Docker required
+- **AWS Account**: Required for pulling container images from our ECR registry
+
+## Prerequisites
+
+- Active enterprise contract with AssemblyAI
+- AWS account credentials for container registry access
+- Linux environment with Docker installed
+- NVIDIA Container Toolkit for GPU support
+
+## Setup and deployment
+
+### 1. Docker runtime with GPU support
+
+**1.1** Verify NVIDIA drivers are installed:
+```bash
+nvidia-smi
+```
+
+**1.2** Install NVIDIA Container Toolkit:
+
+Follow the [NVIDIA Container Toolkit installation guide](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) to set up GPU support for Docker.
+
+**1.3** Verify the Docker runtime has GPU access:
+```bash
+docker run --rm --gpus all nvidia/cuda:11.8.0-base-ubuntu22.04 nvidia-smi
+```
+
+### 2. Obtain credentials
+
+**AWS ECR Access**: AssemblyAI will manually provision AWS account credentials for your team to pull container images from our private Amazon ECR registry. Contact your AssemblyAI representative to obtain these credentials.
+
+### 3. AWS ECR authentication
+
+Authenticate with AWS ECR using the provided credentials:
+
+```bash
+aws ecr get-login-password --region us-west-2 | docker login --username AWS --password-stdin 344839248844.dkr.ecr.us-west-2.amazonaws.com
+```
+
+### 4. Pull the Docker image
+
+Pull the self-hosted ML container image:
+
+```bash
+docker pull 344839248844.dkr.ecr.us-west-2.amazonaws.com/self-hosted-ml-prod:release-v0.1
+```
+
+### 5. Obtain license file
+
+AssemblyAI will provide a license file (`license.jwt`) that is required to run the container. The license file contains:
+- Expiration date
+- Usage limits
+- Customer identification
+
+<Callout type="warning">
+The license file provided for testing is valid for 30 days. For production deployments, contact AssemblyAI to obtain a production license.
+</Callout>
+
+### 6. Run the container
+
+Start the self-hosted ML container with GPU support:
+
+```bash
+docker run --gpus all -p 8000:8000 \
+  -e NVIDIA_DRIVER_CAPABILITIES=all \
+  -v /absolute/local/path/to/license.jwt:/app/license.jwt \
+  344839248844.dkr.ecr.us-west-2.amazonaws.com/self-hosted-ml-prod:release-v0.1
+```
+
+**Parameters explained**:
+- `--gpus all`: Enables GPU access for the container
+- `-p 8000:8000`: Maps port 8000 from the container to the host
+- `-e NVIDIA_DRIVER_CAPABILITIES=all`: Enables all NVIDIA driver capabilities
+- `-v /absolute/local/path/to/license.jwt:/app/license.jwt`: Mounts the license file into the container
+
+<Callout type="info">
+Replace `/absolute/local/path/to/license.jwt` with the actual absolute path to your license file on the host system.
+</Callout>
+
+## Using the API
+
+Once the container is running, you can interact with it using HTTP requests.
+
+### Check container health
+
+Verify that the container is ready to accept requests:
+
+```bash
+curl "http://localhost:8000/health"
+```
+
+A successful response indicates the container is ready to process transcription requests.
+
+### Transcribe an audio file
+
+Submit an audio file for transcription:
+
+```bash
+curl -X POST "http://localhost:8000/predict" \
+  -F "file=@/path/to/file.mp3" \
+  -F 'payload={"language": "en"}'
+```
+
+**Parameters**:
+- `file`: The audio file to transcribe (supports common audio formats like MP3, WAV, M4A, etc.)
+- `payload`: JSON object containing transcription parameters
+  - `language`: Language code for the audio (e.g., `"en"` for English)
+
+**Example response**:
+```json
+{
+  "text": "This is the transcribed text from your audio file.",
+  "words": [
+    {
+      "text": "This",
+      "start": 0,
+      "end": 200,
+      "confidence": 0.98
+    }
+  ]
+}
+```
+
+## Supported languages
+
+The self-hosted async solution supports multiple languages. Specify the language code in the `payload` parameter when making transcription requests.
+
+Common language codes:
+- `en`: English
+- `es`: Spanish
+- `fr`: French
+- `de`: German
+- `it`: Italian
+- `pt`: Portuguese
+- `nl`: Dutch
+
+For a complete list of supported languages, contact your AssemblyAI representative.
+
+## Troubleshooting
+
+### Container fails to start
+
+**Issue**: Container exits immediately after starting.
+
+**Solution**: Verify that:
+1. The license file path is correct and the file exists
+2. The license file is not expired
+3. GPU drivers are properly installed (`nvidia-smi` should work)
+4. NVIDIA Container Toolkit is installed
+
+### Health check fails
+
+**Issue**: The `/health` endpoint returns an error or times out.
+
+**Solution**: 
+1. Wait a few moments for the container to fully initialize
+2. Check container logs: `docker logs <container_id>`
+3. Verify GPU access: Ensure the container can access the GPU
+
+### Transcription request fails
+
+**Issue**: The `/predict` endpoint returns an error.
+
+**Solution**:
+1. Verify the audio file format is supported
+2. Check that the `language` parameter is valid
+3. Ensure the file path in the curl command is correct
+4. Review container logs for detailed error messages
+
+## Support
+
+For technical support or questions about the self-hosted async solution, contact your AssemblyAI representative or reach out to the AssemblyAI support team.
+
+## Simplified installation
+
+AssemblyAI is working on packaging solutions and installation scripts to simplify the deployment process for customers. For the latest information on simplified installation options, contact your AssemblyAI representative.