Bit Stew is a relatively new (and, I must add, poorly named) vendor that was built with the intention of creating a platform to handle data requirements for the Internet of Things (IoI). Bit Stew offers data integration, analysis, and predictive automation across a horizontal platform. The platform automates data ingestion, applies machine intelligence to learn patterns in the data, allowing industrial companies to discover actionable insights that optimize operational performance.
Increasingly, however, these broad horizontal offerings don’t meet the real requirement that organizations have, and businesses in the industrial arena are looking for vertical-specific solutions that come pre-tailored for their particular use case. This trend makes perfect sense. A broad IoT platform is, by its very nature, non-specific and requires a lot of work to contextualize it for real-world use. Increasingly, organizations want that contextualization to be offered out-of-the-box.
So it is interesting to see Bit Stew partner with GE (which is, it must be said, an investor in the company) to deliver some of these verticals. The two organizations are targeting a few verticals: oil & gas, aviation, and manufacturing. We’ve long heard from GE about just how applicable the IoT is to its aviation business, as the aspirational example in the press materials goes:
“An airplane engine, monitoring the output of all its systems, notes that it is operating at 90% efficiency and isn’t due for a tune up for another two weeks. Based on rules, algorithms and machine learning, the engine then contacts a central airline monitoring station, schedules an out-of-sync tune up, alerts the airline fleet management system to stage a replacement plane and creates a specific work order for the mechanic that will be conducting the service of the engine.”
In the Aviation sector, Bit Stew’s technology is apparently in an active deployment with one of the largest airlines in the world, ingesting the real-time operational data of more than 900 planes within the airline’s fleet. By ingesting all data pertaining to current and historic engine performance, the airline is hoping to be more able to automate the ongoing maintenance needs of the aircraft. The Asset Performance app ensures that all operational functions of the aircraft are maintained at peak efficiency.
In Manufacturing, the initial pilot integrates instantaneous operations data of manufacturing equipment in 156 individual manufacturing plants for a large multinational manufacturer. All equipment within these plants sends ongoing performance feeds in multiple formats to a dedicated ingestion point managed by Bit Stew, where data formats are instantaneously ingested and standardized to provide both local and holistic operational insights to the manufacturer to optimize ongoing output.
In terms of the oil & gas vertical product, the solution helps oil & gas companies gain real-time intelligence across their environments by automating and managing the data ingestion and the rapid integration of industrial deployments. The platform meets the technical requirement of correlating sensor, geospatial, and work order data. This provides the operator with a semantic understanding for real-time risk analysis of equipment based on current and historic asset performance.
In one example, Bit Stew’s platform modeled, mapped, indexed, and correlated an Oil & Gas data set in less than five hours compared to six man months that relied on traditional approaches such as data historians, data mapping technologies, and open-source data stores.
All of these case studies sound interesting and show that there is much to be gained by moving beyond the easier to build but less applicable horizontal IoT platforms. GE obviously has a massive existing footprint in the aviation, manufacturing, and oil & gas industries, and it is a logical move for Bit Stew to leverage those to build out specific solutions.