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The authors would also like to thank Karan Bhandarkar, Sue Cha, Yash Shah and Nieves Garcia for their contributions in making this initiative possible. If you process millions of email messages daily, fine-tuning Amazon Nova models can help you automate accurate data extraction while reducing costs and hallucinations. Parcel Perform, a leading AI Delivery Experience […]

Google UK shares its latest Economic Impact Report and how to enable more people to unlock the benefits of AI-powered technologies. ​ 

Amazon Quick Sight is a core feature within Amazon Quick — an agentic, AI-powered digital workspace designed to maximize end-user productivity— that provides AI-powered BI capabilities through natural language queries, interactive dashboards, and embedded analytics from trusted enterprise data sources. Amazon Quick Sight assets such as dashboards, analyses, datasets, and data sources can be backed up using the

A scanned yearbook page contains 176 printed names, 4 portrait photographs, and zero machine-readable structure linking them. To digitize this page, you need reliable photo detection with bounding boxes and accurate name extraction. You also need a way to determine which name belongs to which face based on page layout. In this post, we show

At PAR Technology Corporation, we build technology for the restaurant industry, supporting over 300 restaurant businesses, from independent operators to large, multi-brand franchise groups. Across this diverse customer base, we help organizations make better decisions by unlocking the value of their data. When we set out to build a natural language text-to-SQL agent for self-serve

Manually processing paper-based forms remains a significant cost in the healthcare industry. Despite advancements in data extraction of scanned documents and images, human oversight is usually still needed. Entry error by the individual creating the form or lower-confidence extractions from the digitization still must be remediated. In this post, we show you how to build

Production artificial intelligence (AI) agents can fail silently. They may return plausible but incorrect answers, enter infinite reasoning loops, or select the wrong tools without triggering error alerts. These failures make debugging production agent behavior difficult because standard logs and metrics do not capture how decisions are made. Amazon Bedrock AgentCore Observability addresses these debugging

A Google expert explains what it means to take a full-stack approach to AI and why it’s been the foundation of our AI work for so long. ​ 

Picture this: a compliance officer needs a specific clause during an audit, an attorney needs contract terms while a client waits on the phone, or a finance analyst needs numbers from last quarter’s report before a meeting that starts in 10 minutes. In each case, waiting for a scheduled job to finish is not practical.

Insurance is an $8 trillion global industry burdened by manual workflows and a growing talent shortage. Cara delivers an AI-native solution on AWS that automates back-office processes for insurance brokerages. Insurance agents routinely spend hours on repetitive tasks. These include completing applications, analyzing policy coverages, re-keying data across systems, and relaying information between clients and