Abhishek Gupta builds and deploys production-grade AI systems at The Modern Data Company, working across data pipelines, machine learning models, and agentic AI workflows. His work focuses on applying advanced ML techniques to real-world business problems such as forecasting, churn prediction, and supply chain optimization, while exploring emerging paradigms in multi-agent systems, retrieval-augmented generation, and large language models.
Abhishek Gupta builds and operationalises intelligent systems at The Modern Data Company, focusing on taking machine learning from experimentation to production. His work spans data pipelines, model development, and deployment, with a strong emphasis on real-world applicability. He is also associated with Modern Data 101, contributing to conversations around modern data and AI systems.
He has worked on enterprise use cases such as forecasting, churn prediction, and supply chain optimization, applying techniques like ensemble modelling, survival analysis, and hybrid architectures. Through his contributions, including those aligned with Modern Data 101, he brings practical insight into how these systems drive measurable outcomes in production environments.
His current focus is on agentic AI systems, where he designs multi-agent workflows and builds retrieval-augmented generation pipelines using semantic search and vector embeddings. He actively experiments with frontier models, contributing to evolving approaches in intelligent system design.
His work reflects a strong focus on end-to-end system thinking, covering everything from data ingestion to model explainability and performance, enabling the development of scalable and production-ready AI systems.
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