DigitalOcean

Overview DigitalOcean is an AI-native cloud platform that provides a unified infrastructure stack spanning silicon, compute, inference, agents, and data services. It aims to simplify production AI deployment for companies that would otherwise stitch together multiple cloud vendors. The platform targets AI teams, startups, and SMBs who need GPU access, model inference, and managed cloud primitives under a single API, CLI, and billing system. DigitalOcean owns its hardware end-to-end, which it says passes cost optimizations to customers as they scale. Key Benefits Workato reported 67% lower cost running 1 trillion automation tasks on DigitalOcean's Inference Engine versus prior infrastructure. Character.ai handles 1 billion queries per day with 2× production inference throughput on AMD Instinct GPUs through DigitalOcean. Hippocratic AI achieved 40% lower end-to-end P99 latency and 2× higher throughput for 20 million patient interactions. Sub-second Time-to-First-Token (TTFT) and 3.9× higher output speed versus AWS Bedrock on DeepSeek V3.2 per independent Artificial Analysis benchmarks. Monthly spending caps and flat per-unit pricing eliminate surprise bills across all services. How It Works A user signs up, selects a compute product (GPU Droplet, App Platform, or serverless Function), and deploys code or a model via DigitalOcean's CLI or API. For AI workloads, the user calls the Inference Router endpoint with their prompt; the router automatically selects the best model from over 70 choices or directs the call to a dedicated GPU. All resources — compute, storage, networking, agents, and data — are managed through a single control panel and billed on one invoice. Use Cases AI product teams running real-time agent systems that need low-latency inference and persistent memory without cross-vendor data hops. Healthcare AI providers serving millions of patient interactions with strict latency requirements and compliant infrastructure. High-traffic consumer platforms handling over 1 billion daily inference queries on dedicated GPU clusters. Startups and SMBs building web applications on fully managed App Platform or Kubernetes without hiring infrastructure engineers. Data teams running managed databases (PostgreSQL, MySQL, MongoDB, Valkey, OpenSearch) alongside analytics and AI workloads on the same cloud. Developers evaluating model quality by running LLM-as-a-Judge evaluations on any inference endpoint before production deployment. Why Choose This Product DigitalOcean suits teams that want one provider for both traditional cloud workloads and production AI inference, especially those sensitive to cost per token or per GPU hour. The platform explicitly builds for users who prefer open models, open-source tooling, and avoiding vendor lock-in across multiple cloud services.