RAG (Retrieval-Augmented Generation) for Field Service ManagementExploring Key Information Retrieval Dimensions in Field Service Management with RAG: Relevance, Similarity, Relationship, and Structure.Oct 8Oct 8
Enhancing Field Service Efficiency: The Power of Multimodal Virtual AssistantsIn today fast world with many technologies, field service technicians are very important for industries ranging from HVAC to…Jun 22Jun 22
Using NLP (Natural Language Processing) to Improve Field Service Operations.Making Customer Requests and Service Engineer Reports More Efficiently Using AI NLP Techniques.May 12, 2023May 12, 2023
Generative AI — Figuring It Out Through Use Cases in Field Service.How generative tools like AI chatbots could help companies in the field service industry.Jan 15, 2023Jan 15, 2023
Good Models (on their own) don’t generate sufficient valueHow to realize business value from highly performant models, using a case study in the field service industry.Jun 9, 2022Jun 9, 2022
Evaluate the impact of prediction models in practice for field service managementOne of the primary objectives in deploying a predictive model is to assess how and whether the model resolves our business problem…Nov 21, 2021Nov 21, 2021
Explainable AI (XAI) in Field Service Management.How to explain our machine learning models to the stakeholders, following an example of a model that predicts SLA breaches.Apr 11, 2021Apr 11, 2021
Applying the Machine Learning Process for Better Service ResolutionsIn this article we go through the machine learning process yourself in order to answer the most important question ever asked in a field…Jan 10, 2021Jan 10, 2021
Practical Applications of Machine Learning and AI in Field ServiceAugmenting service business with intelligent systems can be useful in enhancing organizational performance.Aug 17, 2020Aug 17, 2020
