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Anyshift provides AI context for your infrastructure, powered by Annie—an AI infrastructure assistant trained on your environment. From answering complex infrastructure questions to suggesting Terraform code and catching hidden issues, Annie helps teams manage, monitor, and optimize their infrastructure with ease and precision. Unlike generic AI copilots, Anyshift provides context-aware insights based on your actual infrastructure and codebase—not just LLM guesses.

Just like every impressive building starts with a strong foundation, every remarkable capability in an AI agent can be traced back to its framework. AI agent frameworks or agentic AI frameworks make it possible to create smart, efficient AI agents that can serve as simple chatbots, facilitate agentic automation, or contribute to complex use cases in finance, supply chain, healthcare, manufacturing, and robotics as part of a multi-agent system. But what are AI agent frameworks?

Process automation has been around for decades, but the tools under this technology umbrella have multiplied over the years. Robotic process automation (RPA) was an early tool for handling simple, routine tasks, and it’s still powerful to have in your intelligent automation arsenal. But when technologies like intelligent document processing, business rules, and workflow orchestration entered the scene, they brought new capabilities to the process automation suite.

Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to large language models (LLMs). It’s becoming a foundational layer in many AI-native workflows, especially when working with real-time or continuously updating data sources. We're excited to announce that Choreo now supports the deployment of MCP servers, empowering developers to integrate AI capabilities more efficiently into their applications.

The generative AI hype train doesn’t appear to be slowing down, with organizational adoption rising from 33% in 2023 to 78% by the end of 2024. In fact, bigger companies are leading the way in GenAI adoption, with the global AI market projected to grow annually by 36.6% between 2024 and 2030. However, GenAI growth isn’t following a linear path. Organizations are utilizing different AI approaches, depending on their specific use cases.

Your organization may be one of the many that is rushing to implement AI. But do you know where you fall on the AI maturity model? More than just a framework for understanding AI, the AI maturity model is a strategic guide that helps turn AI investments into tangible business results. A 2024 IDC study commissioned by Microsoft titled “The Business Opportunity of AI” found that organizations gain a $3.7x return for every $1 spent on generative AI.

Today, we are excited to announce our partnership with Pruna AI. Pruna AI is the optimization engine built to simplify and accelerate scalable inference. Koyeb offers a serverless cloud platform for teams to deploy ML and AI models on high-performance GPUs, CPUs, and accelerators - globally. By combining Pruna with Koyeb, you can speed up your model optimizations, achieve 5x faster inference speeds, and run them on scalable, high-performance serverless infrastructure.