Amazon Quick Enhances Efficiency for Finance, Sales, and Supply Chain Management

AWS has launched the Agentic Data Operations Platform (ADOP), a reference architecture built on Amazon Bedrock, to automate data engineering tasks and reduce the time spent on setting up new data sources from weeks to hours. This platform uses specialized AI agents to generate ETL code, quality checks, and semantic models, aiming to improve efficiency and compliance in data operations.

Amazon Quick has released extensions that embed its agentic AI assistant directly into Microsoft Word, Excel, PowerPoint, and Outlook. This integration allows users to access connected data sources and perform document editing actions within their existing Microsoft 365 workflows, aiming to streamline tasks that previously required compiling information from disparate systems.

Google's BigQuery has achieved up to 35% better query performance and a 40% reduction in query processing costs in 2025. These improvements are driven by autonomous query processing, including history-based optimizations, to better support agentic AI workloads.

Formula 1 (F1) partnered with AWS to implement a Data Accelerator solution that uses agentic AI on Amazon Bedrock AgentCore, reducing data source onboarding time from up to eight weeks to approximately 40 minutes. This change addresses F1's previous 18-month backlog for integrating new data sources into its Customer 360 MarTech platform, improving data operations efficiency and quality.

Amazon Quick has launched the Agentic Catalog Experience, integrating directly with upstream data catalogs like AWS Glue and Databricks Unity Catalog. This update allows AI products to consume and reason over definitions, relationships, and governance metadata, improving the accuracy and efficiency of natural language analytics.

Amazon Quick can automate customer retention workflows, reducing the time to identify and contact dissatisfied customers from days to minutes. This automation helps prevent churn by quickly analyzing customer satisfaction data and generating tailored retention offers.

Jefferies, an investment banking firm, implemented an agentic AI trade assistant on AWS to provide real-time data analysis for its equities trading desks. This solution addresses the challenge of traders needing immediate insights from vast datasets without coding skills or relying on IT for custom dashboards.

Amazon Quick and NVIDIA NeMo Agent Toolkit now enable specialized agent workflows for supply-chain operations. This integration allows users to transition from data dashboards to actionable mitigation recommendations, enhancing decision-making efficiency in enterprise settings.

Tradeshift has migrated from its legacy business intelligence tool to Amazon Quick, improving data processing speeds and reducing costs. The shift allows for faster query responses and broader analytics capabilities, enabling actionable insights from data.

Amazon Quick is an AI tool designed to optimize sales efforts by minimizing time spent on administrative tasks. It assists sales representatives in prioritizing leads, managing CRM updates, and streamlining communications, ultimately aiming to increase productivity and deal closure rates.

AWS Finance teams significantly reduced time spent on data preparation by adopting Amazon Quick, a generative AI assistant. This tool automates complex data queries and analytics, enabling teams to focus on strategic analysis.