AI

Evaluating AI Agents: A production blueprint with Strands and AgentCore

This post was co-written with Motorway and the AWS Prototyping and AI Customer Engineering (PACE) team. Motorway, a UK-based online car marketplace, runs a daily auction where up to 8,000 dealers bid on up to 2,500 vehicles. Motorway worked with AWS Prototyping and AI Customer Engineering (PACE) to build an AI-powered dealer stock search agent

Evaluating AI Agents: A production blueprint with Strands and AgentCore Read More »

Building trade assistant: How Jefferies optimized front office trading operations with AI

If you manage a front office trading desk at investment banks, you know the challenge: traders need real-time insights into client behavior, trade patterns, and market trends from vast amounts of data to make split-second decisions. However, they rarely have the time during the day, nor the coding ability, to build and maintain systems capable

Building trade assistant: How Jefferies optimized front office trading operations with AI Read More »

Building multi-Region visualizations with Highcharts in Amazon Quick

When your carrier performance data spans multiple regions, your dashboard must reconcile fundamentally different competitive structures within a single view. For example, in the US, you rank three carriers (Carrier 1–3) across 49 states and hundreds of metro markets. In the UK, you’re comparing four carriers (Carrier 4–7) across a separate set of national regions.

Building multi-Region visualizations with Highcharts in Amazon Quick Read More »

Detecting silent agent failures with Amazon Bedrock AgentCore optimization

If you’re operating AI agents at scale, Amazon Bedrock AgentCore surfaces a category of insights you’ve probably experienced but struggle to detect: your dashboards show green across the board. 99% completion rate, healthy latency, zero error spikes. And yet customer complaints trickle in about incorrect outcomes. An order modification that was never actually executed. A

Detecting silent agent failures with Amazon Bedrock AgentCore optimization Read More »

Agentic retrieval for Amazon Bedrock Managed Knowledge Base

Your users ask multi-part, comparative, and exploratory questions that span PDFs, slides, tickets, transcripts, and web content. Classic single-shot retrieval breaks down on these questions. Answers miss context, support tickets escalate, and analysts waste hours re-running searches. Agentic retrieval for Amazon Bedrock Managed Knowledge Bases is designed for these questions. Consider two questions an analyst

Agentic retrieval for Amazon Bedrock Managed Knowledge Base Read More »

MIT projects selected for funding under US Department of Energy’s Genesis Mission

MIT researchers are set to contribute to the U.S. Department of Energy’s (DOE) Genesis Mission, with 15 collaborative projects among those selected for funding under Genesis Phase I, DOE announced Wednesday. The Genesis Mission, a national initiative, intends to build “the world’s most powerful integrated science discovery platform” by incentivizing cross-sector collaborations that leverage AI, supercomputing, quantum

MIT projects selected for funding under US Department of Energy’s Genesis Mission Read More »