CASE STUDY

Energy company speeds up time-to-market for edge AI solution

A global Fortune 500 energy company has developed an edge AI solution targeting industries such as oil and gas, chemicals, and the water industry. As the solution expands into multiple industries, the company finds that due to different input data and output integration requirements, it needs to develop a dedicated vertical solution for each use case, which significantly slows down its expansion and increases its support requirements.

The company partners with Prescient to provide rapid edge AI solution customization. Prescient’s distributed dataflow software provides hundreds of data connectors to support data ingestion from any data source, data transformation from any data format, and advanced functions such as data cleansing and feature extraction. The customer’s engineering team can build a dataflow in minutes to provide highly quality, consistent data to its AI. In addition, the engineering team can take its AI’s output and perform further post-process and integration functions, increasing the extensibility of its solution.

A huge advantage of Prescient’s solution is improved time-to-market. Previously, the company has to first gather requirements from its customer’s system, build dedicated software to support the data operations, go through a lengthy release process, and then pilot the solution at the customer’s site. With Prescient’s distributed dataflow software, the company can drop the hardware at the customer’s site before even knowing the customer’s specific data requirements. Its engineering team can build the dataflow in the cloud and deploy it to run at the edge as it garthers the requirements from the customer, which can speed up the pilot process by 3-6 months per each customer.


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What You Need to Know

  • Improves time-to-market by 3-6 months per each customer

  • Rapid edge AI solution customization with dataflows in minutes

  • Accommodates different input data and output integration requirements