Agylytyx Launches New IoT Data Analysis Application

Agylytyx, a cloud-based analytic software vendor, has announced a new platform for analyzing Internet of Things (IoT) data.  The Agylytyx Generator IoT platform represents an application of the vendor’s Construct Library approach to the IoT marketplace. Companies can both explore their IoT data and make it actionable much more quickly than previously thought possible, according to Agylytyx.

From PLC data streams archived as tags in traditional historians, to time series data streaming from sensors attached to devices, the Agylytyx Generator aggregates and presents IoT data in a decision-ready format. The company’s Construct Library (“building block”) approach allows decision makers to create and explore aggregated data such as pressure, temperature, output productivity, worker status, waste removal, fuel consumption, heat transfer, conductivity, condensation or just about any “care abouts,” according to the company. This data can be explored visually at any level such as region, plant, line, work cell or even device. The company says its approach eliminates the need to build charts or write queries.

One of the company’s long-time advisors, John West of Clean Tech Open, noticed the Agylytyx Generator potential from the outset. West’s wide angle on data analysis led him to stress the product’s broad applicability. “Even as the company was building the initial product, I advised the team that I thought there was strong applicability of the platform to operational data,” he said. “The idea of applying Constructs to a received data set has broad usage. Their evolution of the Agylytyx Generator platform to IoT data is a very natural one.”

Agylytyx’s focus on industrial process data was the brainchild of one the company’s investors, Jim Smith.  Smith is a chemical engineer with experience working with plant floor data. “I recognized the potential in the company’s approach for analyzing process data,” he sad. “Throughout the brainstorming process, we all gradually realized we were on to something groundbreaking.”

This  approach to analytics attracted the attention of PrecyseTech, a pioneer of Industrial IoT (IIoT) Systems provider for end-to-end management of high-value physical assets and personnel.  Paul B. Silverman, the CEO of PrecyseTech, has had a longstanding relationship with the company. Silverman noted: “The ability of the Agylytyx Generator to address cloud-based IoT data analytic solutions is a good fit with PrecyseTech’s strategy. Agylytyx is working with the PrecyseTech team to develop our inPALM Solutions IoT applications, and we are working collaboratively to identify and develop IoT data opportunities targeting PrecyseTech’s clients. Our plans are to integrate the Agylytyx Generator within our inPALM Solutions product portfolio and also to offer users access to the Agylytyx Generator via subscription.”

“All of our previous implementations – financial, entertainment, legal, customer service – had data models with common ‘units of measure’ – projects, media, timekeepers, support cases, etc.  IoT data is dissimilar in that there is no common ‘unit of measure’ across devices,” said Mark Chang, a data scientist for Agylytyx. “This dissimilarity is exactly what makes our Construct Library approach so useful to IoT data.  The logical next step for us will be to apply machine learning and cluster inference to enable optimization of resource deployment and predictive analytics like predictive maintenance.”

For more information, visit Agylytyx.

Source: Press release provided by the company.