July 2026 Summaries

DigitalOcean's new Evaluations feature allows teams to validate models and inference routers on their own data before deploying them in production, ensuring optimal performance in terms of quality, latency, and cost. This service, part of the DigitalOcean Inference Engine, includes structured LLM-as-a-Judge evaluations, which score models against pre-built and custom metrics such as correctness, completeness, and bias. The platform supports managing datasets, creating reusable evaluation presets, and triggering evaluations programmatically, facilitating integration into continuous integration (CI) pipelines. Teams can access a range of judge models, including those from DigitalOcean's Model Catalog and external imports, with the option to upgrade for premium model access. Evaluations are integrated directly into the DigitalOcean stack, allowing validation against the same endpoints used in production, and are designed to be flexible, scalable, and repeatable as models evolve.