The AI stack for enterprise engineering in 2026
Blog post from Northflank
In 2026, the enterprise AI engineering stack is composed of seven layers, divided into intelligence and infrastructure categories. The intelligence layers, which include foundation models like Claude and GPT, agent orchestration frameworks such as LangChain, and vector databases like Pinecone, determine the capabilities of AI. Meanwhile, the infrastructure layers, including ML pipelines, model serving, sandbox execution, and application deployment, ensure AI applications can be safely and effectively deployed at scale within enterprise environments. Northflank emerges as a key player in managing the infrastructure layers by providing a unified control plane that includes GPU workloads, sandbox isolation, CI/CD pipelines, and governance tools, enabling enterprises to transition from AI pilot projects to full-scale production deployments. This stack allows enterprise teams to integrate AI capabilities into their software development processes, highlighting the growing complexity and scale of deployment demands faced by these teams.
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