Send emails via SMTP relay with Azure Communication Services
We’ve come across multiple cases where customers want to send emails from applications migrated to Azure through some kind of SMTP service. Though we’ve seen customers opting for O365 for SMTP relay, this can create issues due to throttling limitations in Office Service. Also, managing mailbox and license assignment on Office 365 console is a different story; customers would want to have seamless SMTP relay service experience from single console on Azure. In scenarios where you don’t want to modify code and just change the pointing of your SMTP server to Azure, you can now use SMTP relay built into Azure Communication Services' Email. Azure Communication Services supports different types of notifications, and this blog post offers simple step by step instructions for how you can quickly test and then migrate from other services you’re using to native to Azure for better operational experience and support. Create Azure Communication Services Resource First step you’ll need to do is to create a Communication Services resource from the Azure portal. This is a parent service which has multiple notification services inside it (Chat, SMS, Email, etc). Email is one of them. Create an Email resource Add a custom domain Azure Communication Services Email will provide a default domain that looks like this “GUID.azurecomm.net” and allows for a limited volume of email, so if you need more volume limits, we recommend creating a custom domain. Once you add a custom domain, the UI provides you with a TXT file which you’ll need to create in your Name server. This would take 15 minutes to verify the domain Once the domain is verified, create SPF and DKIM records so that your email doesn’t land in junk and ownership is maintained. Once all the records are created the screen would look like this, please ignore the Azure managed domain. You can only have custom domain in the account and doesn’t have to add Azure domain explicitly. Attach custom domain Once the custom email domain is validated, we’ll need to attach the Email service to the Azure Communication Services resource. Create and assign custom RBAC Role for Authentication We’ll be using 587 port to send email which is authenticated SMTP. For authentication we have Entra ID authentication. Create a service principal by going to Entra ID – App registration page. Register the app and create a client secret. Note down Client ID, Tenant ID and Secret value. This will be used in next stage for authentication. We’ll need to create a custom RBAC role which has permission to send email. We’ll clone reader role. And we’ll be adding two actions which is present in Azure Communication service resource provider. Once the Role is created we’ll need to assign this to service principal Test SMTP Relay via Powershell That’s all, now you’ll need to find out the sender email. Which is default DoNotReply@domain.com You’ll need credentials to authenticate to the service. Username is < Azure Communication Services Resource name>. < Entra Application ID>. < Entra Tenant ID> Password is the client secret which you’ve generated. Port that we’ll need to use is 587 SMTP server address is smtp.azurecomm.net Now you can use any third party application to send email via the above parameters. To showcase we can use PowerShell with the same parameters to send emails. Conclusion: I trust this guide helps you in configuring SMTP relay and send emails from your custom application without any change to the application/code. Happy Learning!Wipro and Microsoft combine forces to transform B2C communications in the enterprise
As we round out 2023, it is with great excitement to share that Wipro Limited and Microsoft are working together to help enterprises propel their success in the digital era with intelligent B2C communication solutions. We are enabling a trifecta with industry leaders, Wipro Limited and Microsoft to build formidable customer and communication experiences in financial services, energy and resources, and retail.Accelerate customer outcomes with Azure AI Services and Azure Communication Services
Learn how Azure Communication Services and Azure AI, and Azure Cognitive Search can be used to automate and transform your customer interactions with faster and informed human-centric responses across any communication channel.Teams Phone extensibility powered by Azure Communication Services
Today, CCaaS providers are using Gen AI to improve customer experience by advising human agents and automating workflows. However, interactions are split between UCaaS like Teams and CCaaS systems, limiting Gen AI's potential. Brands want integrated solutions that unify telephony infrastructure for a complete view of customer interactions and robust data handling. Customizability is crucial for integration. On March 17th, 2025, we proudly announce the launch of Teams Phone extensibility powered by Azure Communication Services at Enterprise Connect, allowing CCaaS vendors to seamlessly integrate with Teams Phone to meet brand needs. Teams Phone with Azure Communication Services Azure Communication Services Call Automation and Calling SDK now enable CCaaS developers to extend Teams Phone capabilities into their application. Key benefits of Teams Phone extensibility include: Consolidate Telephony for UCaaS and CCaaS: Simplified setup with no need to configure and administer separate phone systems. Customers can leverage their Teams phone telephony investment for contact center deployments. Gen AI Integration:Utilize AI to streamline processes and empower customer service agents with automation capabilities, with direct access to Azure AI technology. Extend UCaaS Capabilities to CCaaS: Take advantage of Teams Phone enterprise features, including emergency calling, dial plan policies, wide geographic availability of Public Switched Telephone Network (PSTN) connectivity options and much more. Agent Notification handling: Allow data segregation between CCaaS persona and UCaaS persona with the choice of ringing either the Teams standard client or a CCaaS application. Cost Efficiency: Enable ISVs to build cost-effective solutions using existing Teams Phone plans, without adding Azure Communication Services numbers or Direct Routing. Key Features Provisioning for Seamless Integration:Our provisioning capabilities empower CCaaS providers to connect their ACS deployments with customers' Teams tenants, enabling the use of Teams telephony features for a cohesive and efficient communication experience. Emergency Calling: With Azure Communication Services Calling SDK, we bring enhanced emergency calling support for agents who can dial emergency services, provide their location, and receive callbacks from public safety answering points. Leverage Call Automation: Azure Communication Services Call Automation APIs enable CCaaS providers to build server-based and intelligent call flows. Call Routing and Mid-Call Controls: The solution includes advanced call routing capabilities, which enable more efficient call management and escalation to agents. Mid-call controls enable adding participants, redirecting calls, and transferring calls seamlessly. Convenience Recording: Azure Communication Services enables developers to integrate call recording capabilities into Microsoft Teams for CCaaS scenarios, allowing for customized recording processes controlled by CCaaS admins. Get to know more about Azure Communication Services Call Recording here. Conversational AI Integration: Developers can use Call Automation APIs to leverage AI-powered tools, play personalized greeting messages, recognize conversational voice inputs, and use sentiment analysis to improve customer service. Get started today with this QuickStart. ISV Ecosystem At launch, Teams Phone extensibility will be supported by a diverse range of ISV solutions, including Anywhere365, AudioCodes, ComputerTalk, Enghouse, IP Dynamics, Landis, and Luware. These partners expand the reach and functionality of Teams Phone, allowing you to select the best solution for your unique requirements. This flexibility means businesses can improve their telephony setup while experiencing the full power of Teams Phone and Azure Communication Services. Learn more Teams Phone extensibility will be in public preview and available for customers to try soon. To learn more about Teams Phone extensibility and how to develop your own solutions using Azure Communication Services, stay tuned for more resources and announcements at Build 2025 in May. Developers may join the Azure Communication Services TAP program with the following form: Azure Communication Services Technology Adoption Program Registration. We look forward to seeing how our partners and customers leverage these new capabilities to improve their contact center operations. Follow Sean Keegan on LinkedIn for more news about Azure Communication Services!Revolutionize Customer Engagement: Empowering Your Business with Power Virtual Agents
In today's fast-paced digital landscape, the success of your startup or business hinges on effective customer engagement. Discover the game-changing potential of Power Virtual Agents (PVA), a revolutionary conversational AI tool that empowers entrepreneurs. Learn how PVA can transform your customer support, increase responsiveness, and boost engagement, all without the need for coding expertise.
Azure Communications Services and Azure Open AI Reimagine Customer Support and Business Insights
Contact and support centers are often the first point of contact for customers who need assistance, information, or feedback from an organization. That's why many contact centers are looking for ways to leverage artificial intelligence (AI) to enhance their workflows, automate repetitive tasks, and provide faster and better service. In this article we will explore how Azure Communication Services can help contact centers to improve support agent productivity, customer satisfaction, and reduce costs.Build your own real-time voice agent - Announcing preview of bidirectional audio streaming APIs
We are pleased to announce the public preview of bidirectional audio streaming, enhancing the capabilities of voice based conversational AI. During Satya Nadella’s keynote at Ignite, Seth Juarez demonstrated a voice agent engaging in a live phone conversation with a customer. You can now create similar experiences using Azure Communication Services bidirectional audio streaming APIs and GPT 4o model. In our recent Ignite blog post, we announced the upcoming preview of our audio streaming APIs. Now that it is publicly available, this blog describes how to use the bidirectional audio streaming APIs available in Azure Communication Services Call Automation SDK to build low-latency voice agents powered by GPT 4o Realtime API. How does the bi-directional audio streaming API enhance the quality of voice-driven agent experiences? AI-powered agents facilitate seamless, human-like interactions and can engage with users through various channels such as chat or voice. In the context of voice communication, low latency in conversational responses is crucial as delays can cause users to perceive a lack of response and disrupt the flow of conversation. Gone are the days when building a voice bot required stitching together multiple models for transcription, inference, and text-to-speech conversion. Developers can now stream live audio from an ongoing call (VoIP or telephony) to their backend server logic using the bi-directional audio streaming APIs, leverage GPT 4o to process audio input, and deliver responses back with minimal latency for the caller/user. Building Your Own Real-Time Voice Agent In this section, we walk you through a QuickStart for using Call Automation’s audio streaming APIs for building a voice agent. Before you begin, ensure you have the following: Active Azure Subscription: Create an account for free. Azure Communication Resource: Create an Azure Communication Resource and record your resource connection string for later use. Azure Communication Services Phone Number: A calling-enabled phone number. You can buy a new phone number or use a free trial number. Azure Dev Tunnels CLI: For details, see Enable dev tunnel. Azure OpenAI Resource: Set up an Azure OpenAI resource by following the instructions in Create and deploy an Azure OpenAI Service resource. Azure OpenAI Service Model: To use this sample, you must have the GPT-4o-Realtime-Preview model deployed. Follow the instructions at GPT-4o Realtime API for speech and audio (Preview) to set it up. Development Environment: Familiarity with .NET and basic asynchronous programming. Clone the quick start sample application: You can find the quick start at Azure Communication Services Call Automation and Azure OpenAI Service. git clone https://github.com/Azure-Samples/communication-services-dotnet-quickstarts.git After completing the prerequisites, open the cloned project and follow these setup steps. Environment Setup Before running this sample, you need to set up the previously mentioned resources with the following configuration updates: Setup and host your Azure dev tunnel Azure Dev tunnels is an Azure service that enables you to expose locally hosted web services to the internet. Use the following commands to connect your local development environment to the public internet. This creates a tunnel with a persistent endpoint URL and enables anonymous access. We use this endpoint to notify your application of calling events from the Azure Communication Services Call Automation service. devtunnel create --allow-anonymous devtunnel port create -p 5165 devtunnel host 2. Navigate to the quick start CallAutomation_AzOpenAI_Voice from the project you cloned. 3. Add the required API keys and endpoints Open the appsettings.json file and add values for the following settings: DevTunnelUri: Your dev tunnel endpoint AcsConnectionString: Azure Communication Services resource connection string AzureOpenAIServiceKey: OpenAI Service Key AzureOpenAIServiceEndpoint: OpenAI Service Endpoint AzureOpenAIDeploymentModelName: OpenAI Model name Run the Application Ensure your AzureDevTunnel URI is active and points to the correct port of your localhost application. Run the command dotnet run to build and run the sample application. Register an Event Grid Webhook for the IncomingCall Event that points to your DevTunnel URI (https://<your-devtunnel-uri/api/incomingCall>). For more information, see Incoming call concepts. Test the app Once the application is running: Call your Azure Communication Services number: Dial the number set up in your Azure Communication Services resource. A voice agent answer, enabling you to converse naturally. View the transcription: See a live transcription in the console window. QuickStart Walkthrough Now that the app is running and testable, let’s explore the quick start code snippet and how to use the new APIs. Within the program.cs file, the endpoint /api/incomingCall, handles inbound calls. app.MapPost("/api/incomingCall", async ( [FromBody] EventGridEvent[] eventGridEvents, ILogger<Program> logger) => { foreach (var eventGridEvent in eventGridEvents) { Console.WriteLine($"Incoming Call event received."); // Handle system events if (eventGridEvent.TryGetSystemEventData(out object eventData)) { // Handle the subscription validation event. if (eventData is SubscriptionValidationEventData subscriptionValidationEventData) { var responseData = new SubscriptionValidationResponse { ValidationResponse = subscriptionValidationEventData.ValidationCode }; return Results.Ok(responseData); } } var jsonObject = Helper.GetJsonObject(eventGridEvent.Data); var callerId = Helper.GetCallerId(jsonObject); var incomingCallContext = Helper.GetIncomingCallContext(jsonObject); var callbackUri = new Uri(new Uri(appBaseUrl), $"/api/callbacks/{Guid.NewGuid()}?callerId={callerId}"); logger.LogInformation($"Callback Url: {callbackUri}"); var websocketUri = appBaseUrl.Replace("https", "wss") + "/ws"; logger.LogInformation($"WebSocket Url: {callbackUri}"); var mediaStreamingOptions = new MediaStreamingOptions( new Uri(websocketUri), MediaStreamingContent.Audio, MediaStreamingAudioChannel.Mixed, startMediaStreaming: true ) { EnableBidirectional = true, AudioFormat = AudioFormat.Pcm24KMono }; var options = new AnswerCallOptions(incomingCallContext, callbackUri) { MediaStreamingOptions = mediaStreamingOptions, }; AnswerCallResult answerCallResult = await client.AnswerCallAsync(options); logger.LogInformation($"Answered call for connection id: {answerCallResult.CallConnection.CallConnectionId}"); } return Results.Ok(); }); In the preceding code, MediaStreamingOptions encapsulates all the configurations for bidirectional streaming. WebSocketUri: We use the dev tunnel URI with the WebSocket protocol, appending the path /ws. This path manages the WebSocket messages. MediaStreamingContent: The current version of the API supports only audio. Audio Channel: Supported formats include: Mixed: Contains the combined audio streams of all participants on the call, flattened into one stream. Unmixed: Contains a single audio stream per participant per channel, with support for up to four channels for the most dominant speakers at any given time. You also get a participantRawID to identify the speaker. StartMediaStreaming: This flag, when set to true, enables the bidirectional stream automatically once the call is established. EnableBidirectional: This enables audio sending and receiving. By default, it only receives audio data from Azure Communication Services to your application. AudioFormat: This can be either 16k pulse code modulation (PCM) mono or 24k PCM mono. Once you configure all these settings, you need to pass them to AnswerCallOptions. Now that the call is established, let's dive into the part for handling WebSocket messages. This code snippet handles the audio data received over the WebSocket. The WebSocket's path is specified as /ws, which corresponds to the WebSocketUri provided in the configuration. app.Use(async (context, next) => { if (context.Request.Path == "/ws") { if (context.WebSockets.IsWebSocketRequest) { try { var webSocket = await context.WebSockets.AcceptWebSocketAsync(); var mediaService = new AcsMediaStreamingHandler(webSocket, builder.Configuration); // Set the single WebSocket connection await mediaService.ProcessWebSocketAsync(); } catch (Exception ex) { Console.WriteLine($"Exception received {ex}"); } } else { context.Response.StatusCode = StatusCodes.Status400BadRequest; } } else { await next(context); } }); The method await mediaService.ProcessWebSocketAsync() processesg all incoming messages. The method establishes a connection with OpenAI, initiates a conversation session, and waits for a response from OpenAI. This method ensures seamless communication between the application and OpenAI, enabling real-time audio data processing and interaction. // Method to receive messages from WebSocket public async Task ProcessWebSocketAsync() { if (m_webSocket == null) { return; } // Start forwarder to AI model m_aiServiceHandler = new AzureOpenAIService(this, m_configuration); try { m_aiServiceHandler.StartConversation(); await StartReceivingFromAcsMediaWebSocket(); } catch (Exception ex) { Console.WriteLine($"Exception -> {ex}"); } finally { m_aiServiceHandler.Close(); this.Close(); } } Once the application receives data from Azure Communication Services, it parses the incoming JSON payload to extract the audio data segment. The application then forwards the segment to OpenAI for further processing. The parsing ensures data integrity ibefore sending it to OpenAI for analysis. // Receive messages from WebSocket private async Task StartReceivingFromAcsMediaWebSocket() { if (m_webSocket == null) { return; } try { while (m_webSocket.State == WebSocketState.Open || m_webSocket.State == WebSocketState.Closed) { byte[] receiveBuffer = new byte; WebSocketReceiveResult receiveResult = await m_webSocket.ReceiveAsync(new ArraySegment(receiveBuffer), m_cts.Token); if (receiveResult.MessageType != WebSocketMessageType.Close) { string data = Encoding.UTF8.GetString(receiveBuffer).TrimEnd('\0'); await WriteToAzOpenAIServiceInputStream(data); } } } catch (Exception ex) { Console.WriteLine($"Exception -> {ex}"); } } Here is how the application parses and forwards the data segment to OpenAI using the established session: private async Task WriteToAzOpenAIServiceInputStream(string data) { var input = StreamingData.Parse(data); if (input is AudioData audioData) { using (var ms = new MemoryStream(audioData.Data)) { await m_aiServiceHandler.SendAudioToExternalAI(ms); } } } Once the application receives the response from OpenAI, it formats the data to be forwarded to Azure Communication Services and relays the response in the call. If the application detects voice activity while OpenAI is talking, it sends a barge-in message to Azure Communication Services to manage the voice playing in the call. // Loop and wait for the AI response private async Task GetOpenAiStreamResponseAsync() { try { await m_aiSession.StartResponseAsync(); await foreach (ConversationUpdate update in m_aiSession.ReceiveUpdatesAsync(m_cts.Token)) { if (update is ConversationSessionStartedUpdate sessionStartedUpdate) { Console.WriteLine($"<<< Session started. ID: {sessionStartedUpdate.SessionId}"); Console.WriteLine(); } if (update is ConversationInputSpeechStartedUpdate speechStartedUpdate) { Console.WriteLine($" -- Voice activity detection started at {speechStartedUpdate.AudioStartTime} ms"); // Barge-in, send stop audio var jsonString = OutStreamingData.GetStopAudioForOutbound(); await m_mediaStreaming.SendMessageAsync(jsonString); } if (update is ConversationInputSpeechFinishedUpdate speechFinishedUpdate) { Console.WriteLine($" -- Voice activity detection ended at {speechFinishedUpdate.AudioEndTime} ms"); } if (update is ConversationItemStreamingStartedUpdate itemStartedUpdate) { Console.WriteLine($" -- Begin streaming of new item"); } // Audio transcript updates contain the incremental text matching the generated output audio. if (update is ConversationItemStreamingAudioTranscriptionFinishedUpdate outputTranscriptDeltaUpdate) { Console.Write(outputTranscriptDeltaUpdate.Transcript); } // Audio delta updates contain the incremental binary audio data of the generated output audio // matching the output audio format configured for the session. if (update is ConversationItemStreamingPartDeltaUpdate deltaUpdate) { if (deltaUpdate.AudioBytes != null) { var jsonString = OutStreamingData.GetAudioDataForOutbound(deltaUpdate.AudioBytes.ToArray()); await m_mediaStreaming.SendMessageAsync(jsonString); } } if (update is ConversationItemStreamingTextFinishedUpdate itemFinishedUpdate) { Console.WriteLine(); Console.WriteLine($" -- Item streaming finished, response_id={itemFinishedUpdate.ResponseId}"); } if (update is ConversationInputTranscriptionFinishedUpdate transcriptionCompletedUpdate) { Console.WriteLine(); Console.WriteLine($" -- User audio transcript: {transcriptionCompletedUpdate.Transcript}"); Console.WriteLine(); } if (update is ConversationResponseFinishedUpdate turnFinishedUpdate) { Console.WriteLine($" -- Model turn generation finished. Status: {turnFinishedUpdate.Status}"); } if (update is ConversationErrorUpdate errorUpdate) { Console.WriteLine(); Console.WriteLine($"ERROR: {errorUpdate.Message}"); break; } } } catch (OperationCanceledException e) { Console.WriteLine($"{nameof(OperationCanceledException)} thrown with message: {e.Message}"); } catch (Exception ex) { Console.WriteLine($"Exception during AI streaming -> {ex}"); } } Once the data is prepared for Azure Communication Services, the application sends the data over the WebSocket: public async Task SendMessageAsync(string message) { if (m_webSocket?.State == WebSocketState.Open) { byte[] jsonBytes = Encoding.UTF8.GetBytes(message); // Send the PCM audio chunk over WebSocket await m_webSocket.SendAsync(new ArraySegment<byte>(jsonBytes), WebSocketMessageType.Text, endOfMessage: true, CancellationToken.None); } } This wraps up our QuickStart overview. We hope you create outstanding voice agents with the new audio streaming APIs. Happy coding! For more information about Azure Communication Services bidirectional audio streaming APIs , check out: GPT-4o Realtime API for speech and audio (Preview) Audio streaming overview - audio subscription Quickstart - Server-side Audio Streaming
