Hardware/Software DevelopmentNews & Analysis

Infor Coleman AI Digital Assistant Goes Live

AI Digital Assistant

Business software vendor Infor has recently made a slew of AI related announcements at its annual Inforum customer conference held in Washington DC this year. The key among those are the company’s general availability of Infor Coleman Digital Assistant. The Coleman Digital Assistant is designed to provide natural language access to Infor CloudSuite, improving user productivity. The company also introduced its Infor Coleman AI Platform for embedded machine learning models, which it expects to deliver next year.

Coleman, named after the inspiring physicist and mathematician Katherine Coleman Johnson, whose trail-blazing work at NASA helped man land on the moon, was announced in 2017. Coleman Digital Assistant is the first product using the technology to reach the market.

Rick Rider, Infor Coleman Product Director, said, “According to research from McKinsey & Company, the average interaction worker spends nearly 20 percent of their time looking for information or tracking down colleagues for help with specific tasks.¹ With the ability to quickly source data, automate repetitive processes, and help optimize workflows, Coleman can improve the work experience and help make workers more productive. This can result in significant savings for organizations.”

The Infor Coleman Digital Assistant also is expected to be integrated with Amazon Alexa for Business – which provides tools to manage Alexa devices, enroll users, and configure skills with added security across those devices – by the end of 2018.

Speaking about the the Infor Coleman AI Platform that helps in making connected devices smarter, Rider said, “The Infor Coleman AI Platform can help customers better analyze their data and give them the ability to start asking questions they didn’t even know they should be asking. It can automate tasks that were error-prone, which can help organizations save money by avoiding certain issues or taking advantage of specific opportunities more quickly.”

Organizations can work to gain a competitive advantage by creating models from their proprietary data and experiences, and the Coleman platform enables them to pass along advantages, up and down stream, using their AI insights.

Among the capabilities that Infor expects to deliver with its Infor Coleman technology stack are barcode and QR code scanning and custom image training, or image recognition technologies, known as Infor Coleman Vision. Once a user presents Coleman with a scanned barcode or product image, for example, Coleman could return the desired product information and ordering instructions, or any other applicable skill setup through the same Infor Coleman Digital Assistant skill builder.

The company also announced the availability of Infor Internet of Things (IoT) in a multi-tenant deployment. Infor IoT provides IoT sensor data ingestion, securely and at scale, from anywhere. The IoT sensor data is synchronized with Infor EAM Asset information, bringing deeper context via blending of IoT data and asset transactional data, and delivering better exception detection, workflows, reporting, data analytics and artificial intelligence.

Infor IoT is integrated with AWS IoT, which enables customers to take advantage of AWS’s scalability, stability, and security. Additionally, IoT analytics are provided via Birst, a next-generation, cloud-based platform for networked business intelligence. With Birst, companies can aggregate data from hundreds of thousands of IoT devices and model it into consistent metric frameworks. This enables them to track, analyze, and improve operational efficiency, compliance, sales and marketing effectiveness, and more.

“Infor will deliver a step change in complex asset management through this IoT platform, and offer its customer base something that has been unattainable in the past,” said Kevin Price,Technical Product Evangelist and Product Strategist, Infor EAM. “With wide-reaching improvements in energy, efficiency, and performance reliability, organizations can truly understand the condition of a multitude of assets in real-time, through confident aggregation of different sources inside and outside a given solution deployment.”

For example, traditionally it would be nearly impossible to understand the condition of an asset because users would need to track so much data, both historical and future. In buses, this means overlaying historical asset management, work management, reliability, and sustainability data with third party sources. 

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