Build production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. No infrastructure, no headaches—just fast, flexible AI under one developer-friendly platform.
Track every change, refine behavior, and ship confidently. Our integrated tools help you version, evaluate, and optimize agents, all without managing infrastructure.
Create custom knowledge bases or connect external data to power your agents with real-world context. Use built-in data connectors to pull files from AWS S3 and (coming soon) Google Drive and Dropbox--no complex setup required.
Just need the models? We got you. Remove the complexity of integrating LLMs by letting us handle the hosting, key management, and invoicing. Instantly access models from OpenAI, Anthropic, Meta, and leading open-source providers—no setup, no scaling, and no multi-account headaches.
Integrate models from leading providers with a single API key and fixed endpoint. No need to manage multiple accounts or services.
Your data stays within DigitalOcean infrastructure when using open-source models. DigitalOcean will not use your prompts or payloads for model training or third-party analytics.
Skip infrastructure provisioning. Serverless inference scales automatically to meet your traffic, with no idle costs or capacity planning required.
Track usage and costs across all models in one place. Predictable, usage-based pricing with no surprise overages or vendor sprawl.
From your first idea to full-scale deployment, our platform gives you the building blocks to create, power, and scale production-ready AI agents.
Create agents with UI templates or SDKs
Spin up your first agent in minutes using guided no-code templates or dive in with full-code control using flexible SDKs.
Add knowledge bases, data sources, and inference
Connect your own documents, URLs, APIs, or databases as context sources. Use serverless endpoints with models from OpenAI, Anthropic, and more, no infrastructure setup needed.
Evaluate, compare, and monitor agent quality
Use built-in evaluation tools to test prompts, compare models, and help enable safe, accurate outputs. Review logs and traces to continuously improve agent behavior.
Monitor, scale, and automate workflows
Deploy agents into production, integrate with your apps via APIs, and manage versions, safety, and performance at scale with full observability and automation support.
Getting started with DigitalOcean's GradientAI Platform was incredibly easy. We really appreciated the intuitive design... setting up and deploying our first agent took just like a few minutes. This allowed us to quickly implement AI capabilities without requiring extensive setup processes or even specialized expertise from our side. And that was truly a game changer for us.
Benedikt Klinglmayr
Full Stack Developer, Autonoma
From quick-start templates to production-scale workflows, GradientAI Platform supports agents that deliver value across industries and use cases.
Code generation
Code explanation
Debugging assistance
External chatbots
Internal Q&A bots
Support ticket automation
Content creation
Document summarization
SEO optimization
Trend and market analysis
Report generation
Project planning
Fraud detection
Risk assessment
Compliance checks
Data exploration agents
KPI monitoring
Executive briefings
DigitalOcean’s GradientAI Platform continues to evolve, offering developers more flexibility, smarter agents, and easier ways to build with AI. Check out this blog for the latest updates, in-depth tutorials, and helpful demos.
Experience the power of the GradientAI Platform firsthand by chatting with four pre-built example agents tailored for different use cases.
Talk to an agent with deep knowledge of Kubernetes about how to get started.
Stay ahead with the latest product updates, customer success stories, and strategies to get the most out of DigitalOcean.
Join our webinar series to explore new ways to maximize the services you use today—and discover ones you might want to try next!
See how developers and businesses are leveraging DigitalOcean GradientAI Platform to help build industry-changing solutions.
This is a great question, and one that the industry is still figuring out how to answer. Agents sometimes seem synonymous with LLMs and conversational interfaces like ChatGPT. While others take a more strict definition, where an application must have “agency” in order to qualify as agent—i.e. the ability to act independently based on input from a non-human source. At DigitalOcean, we think of agents as more complicated than the LLM itself. It’s an application that is powered by an LLM but also incorporates stateful components like conversational memory and training on one or more data sources (a vector database, or “Knowledge Base”). It may have a human-like role or personality, and it may have a conversational interface, but it may not. We think of agency as a spectrum of autonomy ranging from simple rule-based responses to complex, goal-oriented, and self-improving behavior.
GradientAI Platform simplifies the process of integrating the components of AI Agents and LLM applications, such as prompt management, prompt evaluations, data sources, 3rd-party tools, and conversational memory. Whether you just need simple LLM API calls or you’re building complex, stateful applications, GradientAI Platform makes the process significantly faster than working directly with the individual components. It gives you deep insight into agent performance. And it also simplifies account management and billing, with all costs coming to you on a single invoice, even if you switch LLM models. Plus, you don’t have to host anything yourself or bring your own API keys, like with similar frameworks.
Visibility into agent performance is one of the key value propositions of GradientAI Platform. Think of our Agent Evaluations feature as the test suite in a traditional code project. It allows you to create a set of prompts (like unit tests), and run your agent against them after any change you make to its instructions, knowledge base, functions, routing, or LLM model. Our Traceability feature exposes the reasoning chain behind an output, including user inputs, model outputs, and function call results. If you don’t like the response to one of your test prompts, or you hit an error along the way, Traceability can help you identify the source of the problem. Assuming the agent has a user interface, you can also view feedback data from users who rate the agent’s responses. Conversation Logs (coming soon) allow you to dig into real user conversations to understand how agents are responding. And Citations help you locate which training data informed the agent’s responses.
At DigitalOcean, your data is never used to train our AI or systems, and it’s never sold or shared. If you select open-source models like Mistral, Llama, or DeepSeek, your data stays entirely within DigitalOcean’s infrastructure, and we store only what we need to power your agent or to provide you with troubleshooting features like Conversation Logs.
You have several options for interacting with the agent at every phase of the Agent Development Lifecycle. Within the DigitalOcean console, it takes about two minutes to spin up an agent with an initial set of instructions. You can immediately start prompting the agent from the Agent Playground and make adjustments as necessary. For ongoing testing, Agent Evaluations provides real responses to a set of prompts or benchmarks that you define, and you can choose how often to run your evals. For integration with broader applications, your agent comes with its own API endpoint and endpoint access key. If you want the agent freely accessible to outside applications without your access key, you can set the endpoint status to “public”. Check out this example of integrating a GradientAI Platform agent with Telegram.
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