
Rohit Saadati developed a Multi-Agent Energy Optimization System for the google/adk-samples repository, focusing on AI-driven supply chain optimization in the power and energy sector. He designed and integrated a Supply Chain AI Agent that leverages real-time data, demand forecasts, and external factors to enhance modeling accuracy and scenario evaluation speed. Using Python, BigQuery, and cloud computing, Rohit modularized the AI agent for future extensibility and documented integration points to support broader deployment. His work emphasized collaborative development and robust QA, resulting in a scalable, reusable workflow that enables faster, data-informed decision-making for energy planning and optimization workloads.
March 2026 monthly summary for google/adk-samples: Delivered the Multi-Agent Energy Optimization System feature, introducing a Supply Chain AI Agent that analyzes real-time data, demand forecasts, and external factors to optimize the power and energy supply chain. No major bugs were reported this month; the focus was on reliable feature delivery and QA of the new sample. The initiative increased modeling accuracy, enabled faster scenario evaluation, and established a reusable AI-driven workflow for energy planning, setting the stage for broader deployment across domains. Technologies demonstrated include multi-agent architectures, real-time data processing, AI agent integration, and collaborative development (co-authored commit).
March 2026 monthly summary for google/adk-samples: Delivered the Multi-Agent Energy Optimization System feature, introducing a Supply Chain AI Agent that analyzes real-time data, demand forecasts, and external factors to optimize the power and energy supply chain. No major bugs were reported this month; the focus was on reliable feature delivery and QA of the new sample. The initiative increased modeling accuracy, enabled faster scenario evaluation, and established a reusable AI-driven workflow for energy planning, setting the stage for broader deployment across domains. Technologies demonstrated include multi-agent architectures, real-time data processing, AI agent integration, and collaborative development (co-authored commit).

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