automation

In: Artificial Intelligence

In real-world video and image analysis, businesses often face the challenge of detecting objects that weren’t part of a model’s original training set. This becomes especially difficult in dynamic environments where new, unknown, or user-defined objects frequently appear. For example, media publishers might want to track emerging brands or productsContinue Reading

In: Artificial Intelligence

Intelligent document processing (IDP) is a technology to automate the extraction, analysis, and interpretation of critical information from a wide range of documents. By using advanced machine learning (ML) and natural language processing algorithms, IDP solutions can efficiently extract and process structured data from unstructured text, streamlining document-centric workflows. WhenContinue Reading

In: Artificial Intelligence

Upgrading legacy systems has become increasingly important to stay competitive in today’s market as outdated infrastructure can cost organizations time, money, and market position. However, modernization efforts face challenges like time-consuming architecture reviews, complex migrations, and fragmented systems. These delays not only impact engineering teams but have broader impacts includingContinue Reading

In: Artificial Intelligence

Organizations across industries face challenges with high volumes of multi-page documents that require intelligent processing to extract accurate information. Although automation has improved this process, human expertise is still needed in specific scenarios to verify data accuracy and quality. In March 2025, AWS launched Amazon Bedrock Data Automation, which enablesContinue Reading

In: Artificial Intelligence

Organizations across various sectors face significant challenges when converting meeting recordings or recorded presentations into structured documentation. The process of creating handouts from presentations requires lots of manual effort, such as reviewing recordings to identify slide transitions, transcribing spoken content, capturing and organizing screenshots, synchronizing visual elements with speaker notes,Continue Reading

In: Artificial Intelligence

Fine-tuning of large language models (LLMs) has emerged as a crucial technique for organizations seeking to adapt powerful foundation models (FMs) to their specific needs. Rather than training models from scratch—a process that can cost millions of dollars and require extensive computational resources—companies can customize existing models with domain-specific dataContinue Reading

In: Artificial Intelligence

Vehicle data is critical for original equipment manufacturers (OEMs) to drive continuous product innovation and performance improvements and to support new value-added services. Similarly, the increasing digitalization of vehicle architectures and adoption of software-configurable functions allow OEMs to add new features and capabilities efficiently. Sonatus’s Collector AI and Automator AIContinue Reading

In: Artificial Intelligence

Extracting information from unstructured documents at scale is a recurring business task. Common use cases include creating product feature tables from descriptions, extracting metadata from documents, and analyzing legal contracts, customer reviews, news articles, and more. A classic approach to extracting information from text is named entity recognition (NER). NERContinue Reading

In: Artificial Intelligence

Modern enterprises are rich in data that spans multiple modalities—from text documents and PDFs to presentation slides, images, audio recordings, and more. Imagine asking an AI assistant about your company’s quarterly earnings call: the assistant should not only read the transcript but also “see” the charts in the presentation slidesContinue Reading