DigitalOcean

The platform offers a unified stack for building, deploying, and scaling applications and websites, extending its capabilities to AI‑native workloads. It provides managed agents that run alongside data, inference, and infrastructure layers, eliminating cross‑vendor hops and egress fees. The service includes a core cloud layer with compute, storage, and networking, as well as a dedicated inference engine that supports over 70 open‑weight and frontier models on a single endpoint, with options for serverless, dedicated, or batch execution.

Developers and teams that need to integrate real‑time agents, persistent data stores, and machine‑learning inference can use the platform’s data and learning layer, which offers managed databases, analytics, and open‑source integration points such as pgvector, Qdrant, and LlamaIndex. The inference router optimizes calls across the stack, aiming to improve throughput and reduce latency for high‑volume workloads.

What distinguishes the offering is its five‑layer architecture—managed agents, data & learning, inference engine, core cloud, and infrastructure—presented as a single, open platform. The design emphasizes performance, cost efficiency, and seamless integration across layers, allowing users to scale from small applications to large AI workloads without fragmenting services across multiple providers.