Transforming Workforce And Asset Management With Cloud-Powered Generative AI

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Transforming Workforce And Asset Management With Cloud-Powered Generative AI
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Vikram Takru is the CEO and co-founder of KloudGin, working to create transformative field service and asset management technology. Read Vikram Takru's full executive profile here.

Today’s field service and asset managers understand the challenges of running a large and complex workforce and asset portfolio. The ability to drive continuous improvements is essential to success. Traditional field service management and enterprise asset management systems have become outdated and inefficient as stand-alone products. They have created virtual boundaries across isolated assets and workgroups, resulting in siloed data, tools and processes.

Even when you can deliver relevant information to field crews in near real time, the sheer volume of information related to assets, maintenance records, safety protocols and asset geographic location is overwhelming. Providing the right in-depth information about assets and their history is critical to improving first-time fix rates and the customer experience.

FMs are different than traditional ML models based on their size and overall purpose. With foundation models, instead of gathering labeled data for each model and training multiple models, customers can use the same pretrained FM to adapt various tasks. To solve this problem, we can use a technique called retrieval augmented generation . Using RAG, you can bundle additional external data as context along with the original question in a prompt before sending it to the LLM to get a response. The external data can come from one or more data sources .

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