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    AWS and GenAI Help Fractal Analytics Reduce Call Handling Time by up to 15%

    AWS and GenAI Help Fractal Analytics Reduce Call Handling Time by up to 15%

    The pilot showed a 10-15% reduction in average data retrieval time and a 30% call deflection rate due to self-service capabilities.

    AWS and GenAI Help Fractal Analytics Reduce Call Handling Time by up to 15%
    Sukriti Gupta·
    5 min

    Fractal Analytics, a leading AI solutions provider for Fortune 500 companies, has effectively reduced call handling time by up to 15% using its latest innovation, dubbed Knowledge Assist, on AWS. 

    Traditionally, data retrieval from multiple internal sources is time-consuming and often involves unstructured data, increasing the complexity of queries. With Knowledge Assist, Fractal aims to make knowledge retrieval more efficient within large enterprises.

    It chose to build Knowledge Assist on AWS, leveraging Amazon Bedrock for its generative AI capabilities. In addition to it, Fractal utilised Amazon Elastic Container Service (ECS) for building connectors for Knowledge Assist and Amazon OpenSearch Service for vector/semantic search. The SaaS application layer runs on Amazon Elastic Kubernetes Service (EKS) and AWS Lambda serverless compute.

    “The generative AI space is evolving rapidly. Being able to choose from various LLMs on Amazon Bedrock, which we can swiftly implement or experiment with, along with the ability to use the platform as an API without hosting concerns, helps us experiment and scale faster,” said Fractal Analytics Client Partner for Products and Accelerators Ritesh Radhakrishnan.

    Knowledge Assist adheres to stringent security and privacy standards, protecting data within each client’s network through private endpoints and end-to-end encryption. Personally identifiable information is masked before storage in the analytics layer.

    During a six-month pilot program, nearly 500 knowledge workers in contact centers adopted Knowledge Assist, handling hundreds of thousands of queries monthly and managing complex data from over 10,000 documents across pdf, doc, and ppt formats. The pilot showed a 10-15% reduction in average data retrieval time and a 30% call deflection rate due to self-service capabilities.

    Clients reported improved customer and employee satisfaction, less supervisor involvement, and enhanced upsell opportunities due to more available time on each call. Radhakrishnan explained that customers received faster and better answers, leading to improved customer satisfaction scores (CSAT). Agents experienced less frustration as they no longer needed to search multiple systems for answers.

    Knowledge Assist also enhances compliance by providing the latest information, reducing instances of customers receiving incorrect or outdated information. This leads to a higher level of first-time issue resolution.

    Moving forward, Fractal plans to implement more automated LLM evaluations and generate fresh insights into calls to help clients proactively address recurring issues and reduce call volumes. This continuous innovation in AI-driven solutions underscores Fractal's commitment to improving business outcomes through advanced technology.

    Fractal has been riding the GenAI wave for a long time. The company entered the generative AI space last June by introducing Flyfish, a new all-round generative AI platform for digital sales. Then, it unveiled India’s first Indian languages-based text-to-image diffusion model Kalaido.ai. Currently, it’s also leveraging GenAI for insurance and even transforming the fashion value chain with vision intelligence. 

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