DigitalOcean built genuine AI infrastructure into its cloud platform rather than adding AI features on top of traditional hosting: an Inference Engine offers 70-plus open-weighted and frontier models (including DeepSeek V3.2, Qwen 3, and the Llama family) through an Inference Router that optimizes every call, with serverless, dedicated, and batch inference modes available.
The Managed Agents Layer is what actually separates this from a generic model-hosting service – production agent orchestration integrates directly with data and infrastructure, with native support for OpenCode, LangGraph, CrewAI, and E2B, explicitly positioned around “no cross-vendor hops, no lost context, no egress fees between layers.” That last point matters practically: a typical AI stack spanning separate model, database, and agent-framework vendors accumulates real egress costs and integration friction moving data between them, which DigitalOcean’s integrated layers avoid.
Data and learning infrastructure rounds out the stack – managed databases (PostgreSQL, MySQL, Valkey), knowledge bases, and built-in vector databases with retrieval and embedding infrastructure. Performance claims include sub-second time-to-first-token and 3.9x higher output speed versus AWS Bedrock, with Character.ai reporting 2x production inference throughput and Workato reporting 67% lower cost. Pricing isn’t specified on the homepage – use the pricing calculator or create an account for rates.
