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The Problem
In today's competitive landscape, businesses must prioritize customer experience to stay ahead. Sia Partners’ teams needed to quickly integrate semantic analysis into their product. Back then, they were looking for high-performance solutions that could be implemented quickly to generate fast results. Sia Partners were one of the first companies to identify the need for an AI-driven solution that could analyze online customer reviews and provide real-time insights to optimize points of sale and enhance customer satisfaction.
How did this project get its start?
In today's competitive landscape, businesses must prioritize customer experience to stay ahead. Sia Partners identified the need for an AI-driven solution that could analyze online customer reviews and provide real-time insights to optimize points of sale and enhance customer satisfaction.
What does working with Lettria look like?
Planning
Teams from Lettria and Sia worked together to define the project's scope, set goals, and establish a roadmap. This meant identifying and understanding the key NLP capabilities required for the solution and how they will be implemented.
Development
Lettria's experts worked closely with Sia Partners' engineers to integrate the NLP platform into Deep Review. This involves customizing the platform to meet specific requirements, such as language support, and domain-specific models, and fine-tuning the algorithms for improved accuracy.
Testing
Both teams collaborate to ensure the platform's performance meets the desired benchmarks. This includes assessing the accuracy of sentiment analysis, intention detection, and other NLP features, as well as identifying areas for improvement and optimization.
Deployment
The Deep Review solution powered by Lettria's NLP platform is deployed and made available to clients across various industries. Both teams continue to collaborate in providing support, ensuring the platform remains up-to-date and optimized, and exploring new ways to enhance the solution's capabilities further.
Callout
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