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In: Artificial Intelligence

Recordings of business meetings, interviews, and customer interactions have become essential for preserving important information. However, transcribing and summarizing these recordings manually is often time-consuming and labor-intensive. With the progress in generative AI and automatic speech recognition (ASR), automated solutions have emerged to make this process faster and more efficient.Continue Reading

In: Artificial Intelligence

Businesses rely on precise, real-time insights to make critical decisions. However, enabling non-technical users to access proprietary or organizational data without technical expertise remains a challenge. Text-to-SQL bridges this gap by generating precise, schema-specific queries that empower faster decision-making and foster a data-driven culture. The problem lies in obtaining deterministicContinue Reading

In: Artificial Intelligence

This post is co-written with Taras Tsarenko, Vitalil Bozadzhy, and Vladyslav Horbatenko.  As organizations worldwide seek to use AI for social impact, the Danish humanitarian organization Bevar Ukraine has developed a comprehensive virtual generative AI-powered assistant called Victor, aimed at addressing the pressing needs of Ukrainian refugees integrating into DanishContinue Reading

In: Artificial Intelligence

Enterprises—especially in the insurance industry—face increasing challenges in processing vast amounts of unstructured data from diverse formats, including PDFs, spreadsheets, images, videos, and audio files. These might include claims document packages, crash event videos, chat transcripts, or policy documents. All contain critical information across the claims processing lifecycle. Traditional dataContinue Reading

In: Artificial Intelligence

According to a Gartner survey in 2024, 58% of finance functions have adopted generative AI, marking a significant rise in adoption. Among these, four primary use cases have emerged as especially prominent: intelligent process automation, anomaly detection, analytics, and operational assistance. In this post, we show you how Amazon QContinue Reading

In: Artificial Intelligence

Generative artificial intelligence (AI) applications are commonly built using a technique called Retrieval Augmented Generation (RAG) that provides foundation models (FMs) access to additional data they didn’t have during training. This data is used to enrich the generative AI prompt to deliver more context-specific and accurate responses without continuously retrainingContinue Reading

In: Artificial Intelligence

In the era of AI and machine learning (ML), there is a growing emphasis on enhancing security— especially in IT contexts. In this post, we demonstrate how your organization can reduce the end-to-end burden of resolving regular challenges experienced by your IT support teams—from understanding errors and reviewing diagnoses, remediationContinue Reading

In: Artificial Intelligence

The Amazon Bedrock multi-agent collaboration feature gives developers the flexibility to create and coordinate multiple AI agents, each specialized for specific tasks, to work together efficiently on complex business processes. This enables seamless handling of sophisticated workflows through agent cooperation. This post aims to demonstrate the application of multiple specializedContinue Reading

In: Artificial Intelligence

Amazon Q Business is a generative AI-powered assistant that answers question, provides summaries, generates content, and securely completes tasks based on enterprise data and information. It connects to company data sources, applications, and internal systems to provide relevant, contextual answers while maintaining organizational security and compliance standards. Today, we’re excitedContinue Reading