Systems | Development | Analytics | API | Testing

Today, we’re thrilled to announce that Koyeb has entered into a definitive agreement to join Mistral AI to advance cutting-edge AI infrastructure. Koyeb will bring its platform, technology, and team to accelerate Mistral Compute offering. Compute is designed to provide leading teams across the globe the same state-of-the-art infrastructure Mistral AI uses to build, run, and scale frontier models and AI software.

AI is changing how work gets done. But for many data leaders, it’s also creating a new challenge: managing the cloud bill. As more people (and more AI agents) query data, cloud data warehouse (CDW) spend can spike fast. Costs become harder to predict, and teams end up making tradeoffs—scaling AI insights or staying within budget. That tension creates a real bottleneck on the path to becoming AI-ready.

Last Tuesday, we kicked off our first AI developer meetup of 2026 with a packed room and over 350 signups! This was our first content-focused event since organizing AI Engineer Paris 2025, and it was a great night bringing the AI dev community together to share ideas and learn from some of the most exciting builders in the space. Want to join next time? Follow our global events calendar to stay in the loop. Our meetup's theme was coding agents. We heard from speakers at Koyeb, OpenAI, and LangChain.

Strapi Cloud delivers fully-managed, cloud-hosted instances of Strapi in minutes. With thousands of projects deploying every day, the team needed high-performance infrastructure to provide a seamless, production-ready experience. Strapi wanted to focus on innovation and improving Strapi, not managing infrastructure. In just weeks, Strapi Cloud moved to Koyeb, gaining a serverless, multi-tenant cloud offering with zero operational overhead.

In 2026, as AI models increasingly generate, refactor, and deploy code on their own, developers face a new challenge: how to safely run code they didn’t write. Sandboxes have become the backbone of this new workflow because they are lightweight, secure environments that let teams test, validate, and monitor code without risking production systems.

Many AI analytics platforms force enterprises into an impossible choice: adopt cloud-only solutions that compromise data governance and security policies or forgo AI capabilities entirely. But there’s a significant problem with that: most companies aren’t 100% cloud-based, and those that are vary between whether they operate in the public cloud, private cloud, or a hybrid environment.

At Koyeb, we are building high-performance serverless infrastrcture for AI. Run workloads on serverless GPUs, next-generation AI accelerators, and CPUs. Our platform runs fully isolated, secure microVMs on bare-metal servers around the world with autoscaling, scale-to-zero, and cold starts as low as 250ms. Just like everyone building in AI, 2025 was a busy year for us. We shipped a lot of features and improvements designed to make your AI deployments experience faster, smoother, and more cost effective.

The performance of AI applications depends on its underlying infrastructure. Whether its fine-tuning custom models, performing real-time inference, deploying AI agents, AI workloads require high-performance hardware like Nvidia GPUs or next-gen AI accelerators from Tenstorrent. On top of performance, efficiently running AI workloads in production and at scale is a challenge.