Exploring LLMs for business analytics.
Applying LLMs to call analytics and to workflows for data analysis, dashboards and reporting.
Role: Senior Data Engineer. Stages: Call analytics prototype; analytics and reporting solution built. Selected technologies: Python, LLM workflows and Model Context Protocol.
This work comes from Eslam’s previous consulting experience. It took place within the same assignment as the data platform case.
The context
The assignment included work on how LLMs could be used for call analytics and business data. The work covered two different applications rather than a single finished product.
Call analytics
Eslam prototyped an end-to-end MLOps platform for LLM-based call analytics. This part of the work was a prototype.
Data analysis and reporting
Eslam also built an LLM-based solution using Model Context Protocol for data analytics, dashboards and automated reporting.
Where this experience is relevant
A team exploring a concrete use for LLMs, or assessing how to connect an AI application with data and reporting workflows. The next step should be guided by the task, the quality requirements and the evidence from evaluation.
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