Parslee AI is a software publisher focused on building infrastructure for the emerging field of AI agent development, maintaining its work publicly through its GitHub presence at github.com/Parslee-ai. The publisher's catalog centers on a single flagship product, the Common Agent Runtime, which serves as a deterministic execution layer for AI agents and is distributed in both command-line interface and server configurations. This runtime addresses a fundamental challenge in the agentic AI space: while large language models are inherently probabilistic, production systems require predictable, repeatable, and auditable behavior. By providing a deterministic execution environment, the Common Agent Runtime enables developers to define, run, and supervise agent workflows in which step ordering, tool invocation, and state transitions follow controlled and reproducible patterns rather than unconstrained model improvisation. Typical use cases include orchestrating multi-step automation tasks, integrating agents with external tools and APIs, testing agent behavior in staging environments before deployment, and operating agents in server mode for continuous or on-demand workloads within larger application stacks. The CLI distribution supports local development, scripting, and debugging, allowing engineers to iterate quickly on agent definitions, while the server distribution suits teams that need to expose agent capabilities as managed services. As a publisher, Parslee AI positions itself in the developer tools and AI infrastructure category, targeting software engineers, platform teams, and organizations building agent-based applications who need reliability guarantees that raw model APIs do not provide. Its open development model on GitHub allows users to inspect the source code, track releases, report issues, and contribute improvements, which is particularly valuable for infrastructure components that must earn trust before being embedded into critical systems.
Deterministic execution layer for AI agents (CLI + server).
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