sim

It positions itself as a central intelligence layer that connects AI agents to APIs, databases, and enterprise tools, allowing teams to compose complex automations without writing infrastructure code for each integration.

Agents built in Sim can call external services, use memory, branch based on LLM outputs, and hand off tasks to other agents in a coordinated workflow.

The platform's workflow canvas allows non-engineers to design agent logic visually while giving engineers the ability to drop into code for custom logic or model configuration.

Sim supports multiple LLM backends, allowing different agents in the same workflow to use different models depending on task requirements a cost-efficient architecture where simple classification tasks use smaller models while complex reasoning tasks use frontier models.

Workflows can be triggered via API, webhook, or schedule, making them embeddable into existing product surfaces.

Sim offers a hosted cloud product and an open-source self-hosted version, targeting teams that want to build production AI workflows without managing the orchestration infrastructure themselves.

The platform handles retries, error recovery, observability (logging and tracing of each agent step), and version management for deployed workflows.