Back to Connectors Set up the Azure Blob Storage connector to import conversation recordings, transcripts, and metadata from Azure Blob Storage into Quality AI Express.
The Azure Blob Storage Connector imports conversation recordings, transcripts, and metadata from Microsoft Azure Blob Storage into Quality AI Express on a configurable schedule. Use this connector to analyze interactions from third-party CCaaS platforms.
Section Description Prerequisites Azure storage account requirements and platform setup. Authentication Method How to authenticate the connector using an Azure Storage connection string. Supported Data Types Voice and chat formats and file structure options. Set Up the Connector Steps to create, test, map queues, and schedule the connector. Troubleshooting Fixes for authentication failures, storage access errors, and data processing issues.
Prerequisites Azure Storage Requirements Requirement Description Storage Account Azure Storage account with Blob access subscription. Authentication Connection string. Container Azure Blob container with conversation files. Supported File Types WAV, MP3, JSON, CSV. Maximum File Size 50 MB per file. Timestamp Format ISO 8601 UTC (YYYY-MM-DDTHH:MM:SSZ).
Requirement Description Quality AI Express Connector feature enabled. Agent Setup Agents configured with valid email addresses. Queue Setup Quality AI queues configured and available for mapping. Permissions Access to Connectors configuration.
Authentication Method The connector authenticates with Azure Blob Storage using a connection string.
Connection String
Open the Azure portal.
Navigate to Storage Account .
Go to Security + Networking > Access Keys .
Copy the Connection String for Key1 or Key2 , and use it to configure the connector.
The fields displayed in the connector vary depending on the selected Auth Type .
Supported Data Types Supported Data Types Data Type Format Files per Conversation Analytics Notes Stereo Voice WAV, MP3 1 Complete Analytics, Enhanced Analytics Single dual-channel recording (agent + customer). Mono Voice WAV, MP3 2 Complete Analytics, Enhanced Analytics Separate agent and customer recordings. Mixed audio isn’t supported. Voice Transcript JSON 1 Text Analytics, Complete Text Analytics Pre-transcribed voice conversation. Chat Transcript JSON 1 Text Analytics, Complete Text Analytics Message-level chat transcript.
Storage Structure Options Choose a folder structure for your Azure Blob container before setting up the connector.
Option A: Unified Path container/ ├── metadata.csv ├── audio/ │ ├── conv-123456.wav │ ├── conv-123457-agent.wav │ └── conv-123457-customer.wav ├── chat/ │ └── chat-123459.json └── test.csv
Option B: Separate Voice and Chat Paths container/ ├── voice/ │ ├── metadata.csv │ ├── recordings/ │ └── test.csv └── chat/ ├── metadata.csv ├── transcripts/ └── test.csv
Set Up the Connector Before you begin, verify that your Blob container is ready:
Upload all required files to Azure Blob Storage.
Metadata .csv files contain required fields and valid values.
Mono conversations have separate agent and customer files.
The container and folder paths are available.
A test.csv file exists in each ingestion path.
Blob permissions enable the connector to access the files.
File and folder names shouldn’t contain any spaces or special characters.
Step 1: Create the Connector
Navigate to Quality AI > Configure > Connectors .
Select + Add Connector > Azure Blob Storage > Connect .
Enter a Name for the connector.
Select the Azure Region for the storage account.
Set Authentication Type to Connection String .
Enter the Connection String from your Azure Storage account.
Configure the storage paths:
Unified Path : Enter a single Blob path for both voice and chat data.Separate Paths : Enter a Voice Path and a Chat Path .
Step 2: Test the Connection
Select the Test tab.
Select Test to run the validation checks.
Verify that the following checks pass: Authentication , File Path Access , File Format Validation , and Metadata Validation .
Step 3: Map Queues
Select the Queue tab.
Map each queueId from the .csv files to a Quality AI Express queue. Values must match exactly.
Select Save .
Every queue ID in the metadata file must map to an existing Quality AI Express queue before ingestion can run. Evaluation forms linked to mapped queues determine how interactions are evaluated.
Select the Schedule tab.
Set the Interval Type , Start Date , Repeat Every , and Start Time (UTC).
Select Save to activate the schedule.
After saving, verify the setup is complete:
Verify that the system saved and validated the queue mappings.
Verify that the processing schedule is active.
Verify that the first ingestion job appears in the Log tab.
Verify that the system reports no processing errors.
The setup is complete when all conversations appear in Quality AI Express dashboards and analytics data is available for ingested interactions.
Step 5: Monitor Ingestion Jobs Use the Log tab to monitor ingestion activity.
Column Description Start Time Job start time. Finish Time Job completion time. Uploaded Number of uploaded files. Processing Number of processed files. Job Status Current processing status. View Details Opens job details.
Ingestion is successful when the uploaded and processed file counts match, the job shows as completed, and no errors appear in the job details.
Troubleshooting Authentication Issues Problem Symptom Resolution Authentication Failed Authentication error. Verify the account key, connection string, and storage account name. Re-copy the credentials from the Azure portal and test again. Authorization Header Error Request rejected. Generate a new access key and update the connector configuration.
Storage Access Issues Problem Symptom Resolution Container Not Found Container or path not found. Verify the container name and folder structure. File Not Available Blob access denied. Verify blob access permissions and storage access settings.
File Validation Issues Problem Symptom Resolution File Format Validation Error Unsupported or invalid file format. Verify the CSV metadata structure and required headers. Metadata Validation Error Missing or invalid metadata. Verify required metadata fields and timestamp values.
Data Processing Issues Problem Symptom Resolution Timestamp Validation Error Invalid timestamp format. Use ISO 8601 UTC format (YYYY-MM-DDTHH:MM:SSZ). Queue Mapping Error Queue IDs not mapped. Map all queue IDs before running ingestion.
Processing time depends on file size, audio duration, transcription latency, and AI analysis complexity.
