Reactive Machines

Large language models (LLMs) deliver strong results on general tasks, but they often struggle with specialized work that requires understanding…

Code reviews were always manual and ineffective because of the disconnect between code and product. Developers can review whether the…

In modern development workflows, developers increasingly rely on agentic coding assistants such as Kiro Integrated Development Environment (IDE) to interact…

AI agents are only as powerful as the tools they can access. Whether retrieving customer data from a CRM, sending…

Rare cancer research generates heterogeneous data across genomic sequencing pipelines, clinical trial registries, biomarker repositories, and peer-reviewed literature. Integrating these…

While deploying Model Context Protocol (MCP) servers in production, enterprises need fine-grained access control across servers, observability into which teams…

When you build agentic AI solutions, you face unique operational challenges. Agents make unpredictable decisions, costs spiral unexpectedly, and debugging…

Deploying large language models (LLMs) at scale on Amazon SageMaker AI Inference makes observability a critical pillar of any production…

This solution builds on open source tools including PyTorch, Hugging Face Transformers, and Liger Kernels. The authors would also like…

As ML teams grow, embedding Amazon SageMaker AI MLflow Apps into a custom portal requires a scalable approach to access…