Amazon Connect has launched new agentic AI solutions, aiming to make powerful AI more accessible and...

Living in the Netherlands, I spend a fair amount of time on trains, and that is usually where I catch up on what the builder community is writing. Until now, that meant opening a laptop or squinting at a browser tab on my phone. This week I found myself scrolling through trending articles and checking […]

AWS has launched Amazon Connect Decisions and Talent plus Amazon Quick, expanding its office software push into recruiting and supply-chain business workflows.

Amazon Connect Customer now enables contact center supervisors to receive real-time alerts directly on the dashboard when specific keywords, phrases, or sentiment patterns are detected during live calls and chats, enabling faster intervention and improved customer outcomes. For example, when a customer says "cancel my account" during a call, a supervisor receives an alert on the real-time dashboard, listens to the live conversation while viewing the real-time transcript and sentiment analysis, and coaches the agent over chat to resolve the issue before the customer churns. Amazon Connect Customer real-time conversational analytics alerts on dashboards are available in all AWS commercial and AWS GovCloud (US-West) https://docs.aws.amazon.com/connect/latest/adminguide/regions.html#contactlens_region where Amazon Connect conversational analytics is offered. To learn more about setting up real-time conversational analytics alerts on dashboards, see the https://docs.aws.amazon.com/connect/latest/adminguide/add-rules-for-alerts.html. To learn more about Amazon Connect Customer, the AWS cloud-based contact center, please visit the https://aws.amazon.com/connect/.

Amazon Connect Customer now provides routing step data in the analytics data lake, making it easier for customers to generate insights from routing decisions. Using the data lake, customers can leverage Amazon Athena and Amazon Quick to analyze trends, such as contacts queued and contacts joined at each routing step, without complex data pipelines. For example, an analyst can now report on how contacts progressed through each routing step, identify where agent matching criteria were relaxed, and measure the impact of routing step configurations on wait times and agent utilization. Routing step data is available in all AWS https://docs.aws.amazon.com/connect/latest/adminguide/regions.html#analytics_datalake_region where Amazon Connect Customer data lake is offered. To learn more about Amazon Connect Customer data lake, see the https://docs.aws.amazon.com/connect/latest/adminguide/data-lake-contact-data.html.  To learn more about Amazon Connect Customer, visit the https://aws.amazon.com/connect/. 

Amazon Connect Customer now provides routing step data in the analytics data lake, making it easier for customers to generate insights from routing decisions. Using the data lake, customers can leverage Amazon Athena and Amazon Quick to analyze trends, such as contacts queued and contacts joined at each routing step, without complex data pipelines. For example, an analyst can now report on how contacts progressed through each routing step, identify where agent matching criteria were relaxed, and measure the impact of routing step configurations on wait times and agent utilization. Routing step data is available in all AWS regions where Amazon Connect Customer data lake is offered. To learn more about Amazon Connect Customer data lake, see the Amazon Connect Customer Administrator Guide.  To learn more about Amazon Connect Customer, visit the Amazon Connect Customer website.

Zendesk and Local Measure partnership underscores need for voice and power of AI.

Amazon Connect Customer provides a library of standard metrics. Custom metrics let you go further; defining the measurements unique to your business. But managing them across various instances manually means definitions slowly drift until the numbers no longer align. A metric you can't trust is worse than no metric at all, because people still make decisions on it. Now you define a metric once and manage it programmatically through seven new API operations (CreateMetric, DeleteMetric, DescribeMetric, ListMetrics, SearchMetrics, UpdateMetricContent, and UpdateMetricMetadata) so your definitions stay consistent as you scale across queues, teams, and environments. For example, a customer experience leader noticing a drop in self-service completion rates can define a custom metric that tracks the percentage of interactions where customers abandon and request a live agent within 90 seconds. Using the API, an AI-powered operations assistant can automatically create the metric and publish it to a monitoring dashboard — no manual console work, no definition drift across environments. Every change is tracked in AWS CloudTrail, giving you a complete audit trail.

Learn how to build a voice ordering system for restaurants that answers a phone call and takes an order end to end, with no app, no website, and no sign-in. It uses Amazon Connect for telephony, Amazon Connect Agentic Voice for real-time speech, an Amazon Connect AI agent for reasoning, and Amazon Bedrock AgentCore Gateway to reach backend tools through MCP.

Amazon Connect Customer now supports tag-based access control for custom metrics, so you can govern which users and roles can view, create, or modify each custom metric. As more teams across your organization adopt custom metrics, they end up editing the same shared library. Without controls, one person can change a metric that other teams count on. The usual fix is to give only a handful of people permissions to custom metrics, but that shuts out every other team that wants to start using them.   Now you can tag each metric, then use those tags to set access: a team gets full control of their own metrics, view-only access to another team’s, and no visibility into the metrics you restrict. Search follows the same access rules, so people only see the metrics they’re allowed to view or manage.

Amazon Connect Customer Profiles now offers profile explorer, a new capability that enables organizations to access a unified, customized view of Amazon Connect Customer Profiles. This intuitive interface enables organizations to better understand and engage with their customers across all touchpoints, enhancing the existing Amazon Connect Customer Profiles service by providing real-time user access to customer information, interaction history and AI-powered insights. With profile explorer, users can search and find end customers using multiple identifiers simultaneously, such as email, phone number, or booking references, with real time results. Customer service teams can customize their views to highlight the most relevant information for their specific needs, including demographic data, communication history, behavioral patterns, and segment membership. Profile explorer also provides AI-generated customer summaries that highlight key patterns and deliver personalized behavioral insights, helping organizations make data-driven decisions to improve customer experiences and drive loyalty. Profile explorer is available in US East (N. Virginia), US West (Oregon), Africa (Cape Town), Asia Pacific (Seoul), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt) and Europe (London) AWS regions. AI summary is currently not available in Africa (Cape Town). To learn more, visit Amazon Connect Customer Profiles webpage or see the Amazon Connect Customer Profiles profile explorer documentation page.

Amazon Connect Customer now supports tag-based access control for custom metrics, so you can govern which users and roles can view, create, or modify each custom metric. As more teams across your organization adopt custom metrics, they end up editing the same shared library. Without controls, one person can change a metric that other teams count on. The usual fix is to give only a handful of people permissions to custom metrics, but that shuts out every other team that wants to start using them.   Now you can tag each metric, then use those tags to set access: a team gets full control of their own metrics, view-only access to another team’s, and no visibility into the metrics you restrict. Search follows the same access rules, so people only see the metrics they’re allowed to view or manage.

Amazon Connect Outbound Campaigns now supports WhatsApp, expanding on the WhatsApp Business messaging capabilities that already allow customers to contact your agents. You can now engage customers through proactive, automated campaigns on their preferred messaging platform, delivering timely communications such as appointment reminders, payment notifications, order updates, and product recommendations directly through WhatsApp. Setting up WhatsApp campaigns uses the same familiar Amazon Connect interface, where you can define your target audience, choose personalized message templates, schedule delivery times, and apply compliance guardrails, just as you do for SMS, voice, and email campaigns. Previously, Outbound Campaigns supported SMS, email, and voice channels, while WhatsApp was available only for customers to initiate conversations with your agents. With WhatsApp support in Outbound Campaigns, you can now proactively reach customers through an additional messaging platform while maintaining a unified campaign management experience. You can personalize WhatsApp messages using real-time customer data, track delivery and engagement metrics, and manage communication frequency and timing to ensure compliance. This expansion provides greater flexibility to connect with customers on their preferred platforms while streamlining your omnichannel outreach strategy. This feature is available in all AWS Regions where Amazon Connect Outbound Campaigns is supported. To learn more, visit the https://docs.aws.amazon.com/connect/latest/adminguide/how-to-create-campaigns.html#create-campaigns-channel-configurations.

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