Artificial Intelligence (Page 2)

In: Artificial Intelligence

This post was written with Lucas Dahan, Dil Dolkun, and Mathew Ng from PropHero. PropHero is a leading property wealth management service that democratizes access to intelligent property investment advice through big data, AI, and machine learning (ML). For the Spanish and Australian consumer base, PropHero needed an AI-powered advisoryContinue Reading

In: Artificial Intelligence

In the benefits administration industry, claims processing is a vital operational pillar that makes sure employees and beneficiaries receive timely benefits, such as health, dental, or disability payments, while controlling costs and adhering to regulations like HIPAA and ERISA. Businesses aim to optimize the workflow—covering claim submission, validation, adjudication, payment,Continue Reading

In: Artificial Intelligence

AI agents are evolving beyond basic single-task helpers into more powerful systems that can plan, critique, and collaborate with other agents to solve complex problems. Deep Agents—a recently introduced framework built on LangGraph—bring these capabilities to life, enabling multi-agent workflows that mirror real-world team dynamics. The challenge, however, is notContinue Reading

In: Artificial Intelligence

This post is co-written by Mark Warner, Principal Solutions Architect for Thales, Cyber Security Products. As generative AI applications make their way into production environments, they integrate with a wider range of business systems that process sensitive customer data. This integration introduces new challenges around protecting personally identifiable information (PII)Continue Reading

In: Artificial Intelligence

This post was written with Sarah Ostermeier from Comet. As enterprise organizations scale their machine learning (ML) initiatives from proof of concept to production, the complexity of managing experiments, tracking model lineage, and managing reproducibility grows exponentially. This is primarily because data scientists and ML engineers constantly explore different combinationsContinue Reading

In: Artificial Intelligence

Building an AI agent that can handle a real-life use case in production is a complex undertaking. Although creating a proof of concept demonstrates the potential, moving to production requires addressing scalability, security, observability, and operational concerns that don’t surface in development environments. This post explores how Amazon Bedrock AgentCore helpsContinue Reading

In: Artificial Intelligence

Organizations building custom machine learning (ML) models often have specialized requirements that standard platforms can’t accommodate. For example, healthcare companies need specific environments to protect patient data while meeting HIPAA compliance, financial institutions require specific hardware configurations to optimize proprietary trading algorithms, and research teams need flexibility to experiment withContinue Reading