Breakthrough serverless platform for Agentic AI automation.
Build in Python. Gain Durability, Observability, Scalability by default.
50x more cost efficient than AWS Lambda.
From the creators of Postgres and Apache Spark
Build any AI workflow, short- or long-running, fully automated or human in the loop, any LLM backend--DBOS makes it crashproof, fully observable, and scalable for you.
We’re not kidding, DBOS is effortless.
DBOS executes AI apps orders of magnitude faster than other serverless platforms. Compute time-based pricing--NEVER pay for workflow wait time!
"With DBOS, developers can build applications in days that now take months on conventional platforms."
Decline a fraudulent credit card charge; block further charges; alert customer by SMS.
Forecast a surge in product demand; rebalance inventory in advance; request shipment approvals; initiate shipments and confirm delivery.
Detect a factory machinery performance anomaly; automatically adjust machine settings and notify maintenance.
Forward a large refund request to a human agent for approval; wait for a response.
Unlike AWS Lambda, DBOS does not charge for time your code spends waiting for LLM responses...that adds up to big savings. This benchmark shows the cost difference.
Tutorial showing how to use DBOS and LlamaIndex to build an interactive RAG Q&A engine and serverlessly deploy it to the cloud in just 9 lines of code.
We’ll do our best to cover all bases.
In case you have additional questions about agentic AI, speak with our team.
Agentic AI is the use of AI models to generate plans for executing tasks, and then executing those tasks.
WIth DBOS, you code your AI applications and agentic workflows in Python, just as you normally would, and then add simple decorators which instruct DBOS on how to provide access to them (endpoints) and how to execute them durably with guaranteed exactly-one processing.
Gartner predicts that, by 2028, 15% of all business operations will be automated by agentic AI. Business continuity, customer experience, and other important parts of the business will depend on the successful execution of AI automation workflows.
With so much riding on the success of your AI applications, durability ensures that they execute the way they are intended to, even if they are interrupted by technical glitches, or if they have to wait a long time for humans in the loop.
DBOS makes your AI applications durable by default. By simply adding a few annotations to your Python or TypeScript code, DBOS ensures that workflows execute durably. If they are interrupted, they automatically resume executing where they left off when restarted. Besides ensuring that your agentic AI workflows execute durably, DBOS reduces the amount of coding and technical debt it would normally require to ensure durable execution.
DBOS is a serverless compute platform build for agentic AI. Besides providing a platform on which to host and run your autonomous AI workflows, DBOS makes the following automatic:
Scalability - Scale from zero to millions of requests in seconds--and back to zero when not in use. Only pay for what you use.
Durability - DBOS ensures your agentic AI workflows execute the way the are intended to, no matter what. If they are interrupted by a technical glitch such as an LLM time out or LLM rate limiting, DBOS automatically restarts them and resumes execution from where it left off before the interruption.
Observability - DBOS outputs OpenTelemetry data for your agentic AI workflows, so you have complete visibility into the execution history of your application. It makes troubleshooting, auditing, and AI optimization much easier.
In addition to making your agentic AI applications more durable, scalable, and observable, DBOS is the only serverless platform that does NOT not charge you for time your code spends waiting for backend responses. This saves you a lot of money compared to other platforms like AWS Lambda.
DBOS runs standard Python or TypeScript code. Your applications can interface with any LLM or other backend systems via API calls, or direct access to Postgres-compatible databases via SQL.
DBOS ensures that workflows orchestrating calls to remote services and backend databases always execute durably, with OpenTelemetry observability traces output by default for easy troubleshooting and auditing.