DBOS

Native integrations with Pydantic AI, LlamaIndex, the OpenAI Agents SDK, Google ADK and the Vercel AI SDK make the customer's agent framework durable instead of supplying the tools. They wrap the agent loop as a workflow and each model request, tool call and MCP communication as a checkpointed step, and any step can wrap an outside API call with retries. The tools, credentials and connectors belong to the framework and the customer's code, and DBOS has no connector catalog or framework of its own for authenticated actions.

Sourcedocs.dbos.dev/integrations/pydantic-airead 2026-09-23

Durable orchestration is the product. Workflows and steps are written as ordinary code in Python, TypeScript, Java or Go, with automatic step retries, durable queues carrying concurrency and rate limits, child workflows, durable sleeps and waits, messages and events between workflows, and agent loops (including subagents through the Vercel AI SDK integration) run as workflows.

Sourcedocs.dbos.dev/ai/ai-quickstartread 2026-09-23

There is no retrieval structure DBOS maintains over the customer's corpus. Workflows are checkpointed to the customer's own Postgres, and the Vercel AI SDK integration makes embedding calls durable steps, but the index and retrieval belong to the customer's code.

Sourcedocs.dbos.dev/examplesread 2026-09-23

Human input is handled with a durable wait in the customer's code. In the human in the loop guide, an agent calls DBOS.recv to wait hours or days for a notification with a deadline, checkpointed so the wait survives restarts and upgrades, while DBOS.send delivers the person's response and workflow events publish the agent's status. That is a mechanism the customer's code calls, but it is general durable messaging applied to approval, with no approval step, approver identity, review surface or policy guardrail of DBOS's own, and the gate's logic is the customer's code.

Sourcedocs.dbos.dev/ai/hitlread 2026-09-23

DBOS states SOC 2 compliance, audited regularly, along with GDPR and CCPA, with a HIPAA BAA available and SOC 2 and HIPAA support on Teams. Teams adds role based access control and Enterprise adds SSO and SAML, and Conductor's organization management supports RBAC and any OAuth compatible SSO. DBOS also states that Conductor is off the execution path and never sees workflow data.

Sourcedbos.dev/dbos-pricingread 2026-09-23

Each workflow is recorded step by step. Every step's input and output is checkpointed, and the Conductor console shows workflow state, history and traces, monitors queues in real time and alerts on failures (custom alerting on Teams), with managed retention policies setting how much history each application keeps and for how long. The library emits OpenTelemetry traces and logs, OpenMetrics is supported on Teams, and an MCP server lets the customer's own agents inspect workflows.

Sourcedocs.dbos.dev/production/conductorread 2026-09-23

State is kept inside one run. Every workflow and step is checkpointed to Postgres, so a workflow that crashes resumes from its last completed step and the agent's code carries on from the restored outputs. The scope is one run, so a checkpoint lets the same run finish and carries nothing into the next. Step outputs sit in queryable tables, and Conductor shows the history. There is no state store that persists across runs for each user, conversation or entity as agent memory.

Sourcedocs.dbos.dev/production/retentionread 2026-09-23

The customer decides where DBOS runs. The open source library runs inside the customer's application on any Linux, macOS or Windows host, on premises or in any cloud, against the customer's own Postgres, and Conductor can be self hosted (with Kubernetes guides) and run in air gapped environments on Enterprise.

Sourcedocs.dbos.dev/production/hosting-conductorread 2026-09-23

Quickstarts and an examples library ship in each language, including AI examples such as an agent inbox and a customer service agent. These are examples a developer builds from, not a catalog of agents a customer adopts.

Sourcedocs.dbos.dev/examplesread 2026-09-23

Work starts on its own. Scheduled workflows run exactly once per interval on cron schedules, which can be created at run time and are stored in the database, and durable queues start enqueued workflows as capacity allows.

Sourcedocs.dbos.dev/golang/tutorials/scheduled-workflowsread 2026-09-23

No model runs inside DBOS for a customer to choose. The model lives in the customer's own framework (Pydantic AI, the OpenAI Agents SDK, Google ADK, the Vercel AI SDK), and DBOS checkpoints each model request as a step whatever the model is. Being model agnostic because the model belongs to someone else is different from offering a choice of model.

Sourcedocs.dbos.dev/integrations/vercel-airead 2026-09-23

Outside systems can call DBOS through open source SDKs for Python, TypeScript, Java and Go, a Conductor API with a published OpenAPI specification for managing workflows in code, the dbosctl command line tool, and an MCP server for inspecting workflows.

Sourcedocs.dbos.dev/production/conductor-apiread 2026-09-23

Debugging after a failure is supported. The debugging guide uses the checkpointed history to find where an agent went wrong and workflow fork to restart it from a chosen completed step, reproducing the state up to that point deterministically, in code or from the Conductor UI. That is debugging, not testing. There is no evaluation harness, scored test cases or quality gate of DBOS's own, and the example evaluation step is the customer's own LLM call.

Sourcedocs.dbos.dev/ai/debuggingread 2026-09-23

DBOS operates no browser or desktop for the agent and has no browser automation environment of its own. It makes the customer's code durable wherever it runs.

Sourcedocs.dbos.dev/ai/ai-quickstartread 2026-09-23