Julep is a serverless AI workflow platform that lets data science teams build, iterate on, and deploy multi-step AI pipelines using a simple, declarative YAML-based configuration.

Julep is designed for data scientists and ML engineers—especially in enterprise settings—who want to quickly move from AI prototypes to production without the need for heavy backend engineering.

Julep brings software engineering discipline to AI development using its 8-Factor Agent methodology, treating AI components as proper system elements with model independence, clear tool interfaces, and structured reasoning.

Unlike frameworks like LangChain, which focus on prompt chains, Julep is a complete platform for building production-ready AI systems with complex workflows, state management, and long-running tasks.

You can build multi-step AI workflows that include decision-making, loops, parallel processing, state management, retries, and integrations with external tools and APIs.

Julep automatically scales to handle millions of executions and features robust fault tolerance, state management, and long-running execution capabilities to ensure reliable workflows.

Yes. Julep offers private deployments, robust security measures, and compliance features to meet enterprise needs, ensuring a reliable and production-ready platform.

Julep offers a free tier for experimentation and two paid models: a usage-based pricing model for their cloud platform and dedicated enterprise/on-prem deployments for large organizations.

Julep uses a YAML-based configuration to simplify building, iterating on, and deploying AI workflows, paired with tools for modular design and rapid scaling to streamline development.

Yes, Julep supports seamless integration with existing AI models, data sources, and REST APIs, allowing you to leverage your current technology stack.