LTIMindtree successfully modernized its customer service capabilities and call summarization chatbots by overcoming the time-consuming bottlenecks of manual deep learning model tuning. To eliminate these inefficiencies and boost system accuracy, the company integrated advanced experimentation tooling into its workflow. Critical to maximizing throughput and refining neural network parameters, the SigOpt Intelligent Experimentation Platform empowered data scientists to seamlessly track runs, visualize training trajectories, and execute multi-metric hyperparameter optimization. By combining powerful Intel software tooling with scalable processor hardware, LTIMindtree achieved a double-digit performance improvement, cutting inference time by up to 63 percent while delivering responsive, accura

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