Developed an autonomous agent network that allows analysts to query company data in plain language and receive contextualised answers in seconds. The system reduced reliance on manual reporting by making high quality insights instantly accessible to less technical teams.
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Designed and implemented a large scale data orchestration and validation framework for a telecom data platform, ensuring reliable delivery of highquality datasets to analytics and downstream systems. This project replaced fragmented legacy processes with an automated solution, and enhanced trust in the data.
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Designed and deployed a cloud based recommendation system for a telecom client, enabling personalised offers across TV, broadband, and mobile. Integrated multiple data sources into a unified model and applied machine learning to improve targeting, resulting in increased engagement and faster campaign turnaround.
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Developed a pipeline to analyze customer service call transcripts using LLMs for automated summarization, sentiment analysis, and issue classification. Enabled faster insight generation and quality monitoring by extracting key themes, and customer intent from thousands of conversations.
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