Case Study: Empowering Vulcan Steel with Datacom and Microsoft AI


Microsoft NZ partner Datacom worked with Vulcan Steel to build a workplace safety solution using Microsoft AI and machine learning. Their solution was featured during the Microsoft Build conference in May 2018. Read on to find out more about this collaboration.

Vulcan Steel at MS Build

Congratulations to Vulcan Steel who were showcased at the Microsoft Build conference in Seattle this week! We worked with Vulcan Steel to build a workplace safety solution using AI and machine learning. The concept was originally pitched by James Wells of Vulcan Steel at our #Datacomp hackathon in 2017, then Datacom people brought it to life as a collaboration with James and his team.You can hear more from James on how they realised the vision at our upcoming Techweek event, ‘Emerging Tech for Good – In Action’ Auckland Wellington #FutureValueCreator #AI #artificialintelligence #MSBbuild

Posted by Datacom on Wednesday, May 9, 2018


Vulcan Steel makes about 3,000 deliveries of steel a day to businesses throughout New Zealand and Australia – which means that each day, its employees need to use their training to figure out how to safely get large, heavy and unwieldly pieces of steel off of its trucks and into the hands of a very diverse group of customers.

“It’s an awkward product to transport, and it’s difficult to design out all of the risks,” said James Wells, who acts as the company’s chief information officer. “So essentially what that means for us is one of the key requirements or skills for us to keep people safe is around education.”

For years, Vulcan Steel did what most companies do – they educated their employees about safety before sending them into the field, and then they did additional training as needed if someone reported an accident or near miss.

Now, they’re using artificial intelligence to try to more proactively prevent accidents and near misses before they happen. The company recently started using Microsoft Cognitive Service’s Custom Vision tools to evaluate camera footage from the company’s trucks for actions that could be risky or lead to an accident.

The computer vision tools are able to do what the human eye couldn’t reasonably do – sift through thousands of pieces of footage a day to look for potential risks – freeing up the company’s workers to review just a small subset of footage that has been flagged as a possible concern.

That, in turn, is allowing Vulcan Steel to focus its education efforts on what it sees as the most worrisome or risky scenarios. Wells said accidents were already exceedingly rare, so the goal is to build the company’s culture of safety.

“What we’re hoping is we will measure the number of education discussions that take place as a result,” Wells said. “From our point of view, if we add an additional number of safety discussions to our organization, there’s not really any negative that can come of that.”

Vulcan Steel doesn’t have a large staff of developers, and it certainly doesn’t have a team of AI experts. Wells said the development of this AI-based system was basically the work on one enthusiastic .NET developer who saw the potential for how AI could help the business.

Vulcan Steel employees need to manage many variables when loading and delivering steel orders.

“It’s impressed me, how little detailed experience it’s taken to get to where we are,” Wells said.

At Microsoft’s Build developers conference in Seattle this month, the company is unveiling a series of new and updated tools that are part of its effort to help all developers do what the developer at Vulcan Steel did – incorporate AI into new or existing processes, whether or not they have a background in the fast-emerging field.

Joseph Sirosh, Microsoft’s corporate vice president in charge of Microsoft’s cloud AI platforms, said Microsoft’s expanding roster of AI tools for developers comes as companies are clamoring to add things like speech or image recognition into their applications as a way to stand out from the competition, operate more efficiently and better serve customers.

“What we are seeing is a huge hockey stick in the adoption of AI among all the major applications, and the apps are now starting to be differentiated based on these capabilities.”

At Build, the company’s announcements will include a number of new capabilities for its Microsoft Cognitive Services, which allow developers with little or no AI expertise to add things like speech, language and search capabilities to their applications. The announcements include a unified speech service that includes everything from improved text-to-speech capabilities to custom voice recognition, as well computer vision advances that provide new capabilities for identifying objects, extracting information from images and performing visual searches.

“I hope we spark imagination, and I hope we show them ways to make that imagination come true through the APIs we have.”


Microsoft also will showcase updates to its conversational AI tools, including a public preview of Bot Builder SDK v4, and the capability to do things like add personas to bots, learn conversational patterns and extract questions and answers from documents.

In addition, Microsoft is announcing support for deploying Microsoft Cognitive Services on the edge – or on a device such as a vehicle or camera that doesn’t have a constant connection to a network or the cloud. Microsoft also said it was making updates to Azure Machine Learning Service, which provides lifecycle support for AI development, training and deployment, and it announced ML.NET, which Microsoft already uses internally to more easily incorporate AI into a .NET developer’s existing workflow.

Sirosh said he hopes the Build conference will give developers practical guidance for adding AI tools and learning AI skills – and also get them excited about what they can do with those capabilities.

“I hope we spark imagination, and I hope we show them ways to make that imagination come true through the APIs we have,” Sirosh said. “And then I hope they get inspired to use more advanced machine learning to build their own custom APIs in the cloud.”

You can hear more from the team on how they realised their vision at the “Emerging Tech for Good – In Action” event during Techweek:

Wellington 22 May:

Auckland 23 May:

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