# Evolving From Legacy BI to Agentic AI at Tradeshift with Amazon Quick

> **Platform:** [SPIDITS AI](https://spidits.com/) — Real-Time AI News & Market Intelligence  
> **Published:** 2026-07-20T16:56:48.000Z  
> **Category:** PRODUCT_LAUNCH  
> **Impact Score:** 140/100  
> **Primary Source:** [AWS ML Blog](https://aws.amazon.com/blogs/machine-learning/evolving-from-legacy-bi-to-agentic-ai-at-tradeshift-with-amazon-quick)  
> **Canonical Citation:** [https://spidits.com/timeline/evolving-from-legacy-bi-to-agentic-ai-at-tradeshift-with-amazon-quick](https://spidits.com/timeline/evolving-from-legacy-bi-to-agentic-ai-at-tradeshift-with-amazon-quick)

## Executive Summary
In this post, we describe how Tradeshift deployed Amazon Quick with agentic AI capabilities to replace our legacy BI tool, resulting in query response times.

## Why It Matters (Strategic Analysis)
Crucially, this shifts data operations from manual engineering bottlenecks to automated, natural-language-driven analytics workflows.

## Referenced Coverage & Sources
- **[AWS ML Blog](https://aws.amazon.com/blogs/machine-learning/evolving-from-legacy-bi-to-agentic-ai-at-tradeshift-with-amazon-quick)**: Evolving from legacy BI to agentic AI at Tradeshift with Amazon Quick — _In this post, we describe how Tradeshift deployed Amazon Quick with agentic AI capabilities to replace our legacy BI tool, resulting in query response times..._

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*Synthesized by SPIDITS AI Market Intelligence Desk. Track live AI news, model releases, and funding: [https://spidits.com](https://spidits.com)*