Low-latency and data security are indispensable for any organization and containers take care of both these aspects when using artificial intelligence (AI).

It’s been a year since Microsoft introduced Azure development Services in containers. Needless to say, countless businesses from different industries have gained a competitive edge from this combination. The powerful combination of domain-specific AI service and containers helps enterprises apply AI in the most useful way with Azure as compared to other major cloud providers. From healthcare to financial services, almost every vertical has transformed its processes and customer experiences.

This article sheds light on what Azure cognitive services and containers have achieved together and what we can expect in the near future.

Automation of data extraction in highly-regulated businesses

The growth of enterprises is accompanied by thousands of hours of repetitive but critically important work. Thus, domain specialists end up spending too much of their time on completing this work. Nowadays, innovative organizations use robotic process automation (RPA) to help manage, scale and accelerate processes, thus freeing up people to create more value.

By deploying Cognitive Services in containers, companies can handle massive volumes of data either on-premises or in the cloud while cutting the time required for growth. The BFSI (Banking and Financial Services Industry) and health care are the domains where such combinations work extremely well.

Simplifying disaster relief operations on the ground

You will be amazed to know how Azure can work wonders not just for commercial businesses but also for the entire humanity.

A few years ago, Liberia experienced a deadly Ebola outbreak. A team from USAID was deputed to end the crisis. Once they reached there, their primary task on the ground was to find and categorize different types of information. This included data on the state of healthcare facilities, wifi networks, and population density centers. They had to track everything manually and extract insights from a complex corpus of data to determine the best course of action.

Now, fast forward to the present day. The rugged versions of Azure Stack Edge empower teams to respond to such crises. They can carry a device loaded with Cognitive Services in their backpack. It helps them upload unstructured data like maps, images, pictures of documents and then extract content, translate, draw relationships among entities, and apply a search layer. With these cloud AI capabilities available offline, response teams can find the information they need in the blink of an eye.

In Satya’s Ignite 2019 keynote, Dean Paron, Partner Director of Azure Storage and Edge, made a special mention of how Cognitive Services in Azure Stack Edge can be applied in disaster management.

Detecting anomalies in predictive maintenance

I will explain to you this use-case through a real example of Airbus.

Airbus Defense and Space is one of the world’s largest aerospace and defense companies. It has tested Azure Cognitive Services in containers and developed a proof of concept (POC) in predictive maintenance. They run an Anomaly Detector for immediately spotting unusual behavior in voltage levels and mitigate unexpected downtime. Using advanced anomaly detection in containers reduced the burden on the data scientist team and Airbus can scale this critical capability across the business globally.

“Innovation has always been a driving force at Airbus. Using Anomaly Detector, an Azure Cognitive Service, we can solve some aircraft predictive maintenance use cases more easily.” – Peter Weckesser, Digital Transformation Officer, Airbus

An intelligent virtual agent that delights customers and employees

Again, I will explain this using an example of Lowell, one of the largest credit management services in Europe. It works hard to make every consumer interaction a seamless experience using AI. Thus, Lowell adopted Azure to streamline the outdated processes that occupied the time of the company’s highly-trained credit counselors. It turned to Cognitive Services to create an AI-enabled virtual agent that now handles 40 percent of all inquiries. This makes it easier for service agents to serve customers in a better way.

Due to GDPR requirements, chatbots weren’t considered by many businesses before containers became available. Now companies like Lowell can ensure the compliance of data handling with stringent standards by running Cognitive Services in containers.

Carl Udvang, Product Manager at Lowell, said: “By taking advantage of container support in Cognitive Services, we built a bot that safeguards consumer information, analyzes it, and compares it to case studies about defaulted payments to find solutions that work for each individual.””

Transforming customer support with call center analytics

The previous point shows how AI has improve customer engagement positively. Now, here’s one more application that relates to call center analytics.

There’s no doubt that call centers are a critical customer touchpoint for many businesses. They can derive insights from customer calls and use them to improve their customer support.

Using Cognitive Services, businesses can transcribe calls with Speech to Text, analyze sentiment in real-time with Text Analytics, and develop a virtual agent to respond to questions with Text to Speech.

By transcribing calls, customer service agents can:

• Get real-time feedback on customer sentiment and call effectiveness.
• Batch process data to identify broad themes and unlock deeper insights on millions of hours of audio.
• Integrate with their own custom workflows and scale throughput at low latency.

Summing it up

The capabilities of Azure Cognitive Services, coupled with AI, can only be limited by your imagination. You will come across many such success stories on the web. Going through them will give you a better on how to use Azure services and containers to your advantage.