Ahead of its Open Intelligence Summit in San Francisco, DigitalOcean has announced the launch of its Agent Learning Services and Agent Data Services, expanding its modern agentic cloud stack to enable recursively self-improving AI agents. Designed to resolve the performance plateaus typical of deployed AI agents, the integrated solution allows enterprises to run, learn, evaluate, and optimize autonomous agents within a single, secure environment. The Agent Learning Services suite consists of three interconnected tools: Insights, which records agent activities; Signals, which identifies execution failures or inefficiencies; and Evaluations & Simulations, which rigorously tests proposed optimizations before live deployment. Complementing this framework, DigitalOcean Agent Data Services acts as a managed contextual data foundation, automatically ingesting, redacting, indexing, and organizing structured and unstructured multi-modal enterprise data to feed the agentic feedback loop.
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Emphasizing the strategic significance of this platform update, Vinay Kumar, Chief Product and Technology Officer at DigitalOcean, noted, “The question has changed from ‘can we launch an agent’ to ‘does our agent get better with every run.’ We built Inference Engine so agents could think, Managed Agents so they could act, and now Agent Learning Services and Agent Data Services so they can improve, on one open cloud and on the customer’s own data. That is what owning your intelligence means, and it is why DigitalOcean is the place to launch and scale self-improving agents.” While Agent Learning Services are currently available in public preview, the Inference Router optimizer and Agent Data Services are accessible via private preview.