Julep is a developer platform that provides infrastructure for building stateful, memory-aware AI agents.

Who should use Julep?

It is best for software engineers and developer teams building production-grade agents.

Yes, Julep has an open-source core for local testing, alongside paid cloud plans.

How much does Julep cost?

Paid cloud plans start at $49/month, scaling with usage and API call volumes.

How does Julep handle memory?

It stores session histories and user state in a persistent database layer, keeping agents context-aware.

What should buyers watch for?

Estimate your workflow execution rates, as heavy production volumes will scale usage costs.

Julep

Stateful agent platform and orchestration API for AI developers.

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What is Julep?

TL;DR

Julep is an open-source platform focused on shared memory for teams and AI agents. Its Memory Store connects conversations, notes, decisions, and context across tools such as Claude, ChatGPT, Cursor, Slack, and Codex.

Stateful session memory that persists context across interactions
Durable workflow execution that handles automatic retries and loops
SDK support for Python and Node.js with type-safe APIs

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About

Julep is an developer platform and orchestration API designed to build stateful AI agents. Traditional AI applications rely on prompt-response loops that discard conversation histories and memory once completed. Julep addresses this by managing long-term session memory, user state, and multi-step workflows in a dedicated database layer, allowing agents to retain context across infinite interactions. The product is useful for software engineers, developer teams, and tech startups who need to build assistants that execute complex, long-running tasks. By utilizing Julep, developers can deploy agents that perform lead research, manage customer support tickets, or orchestrate files while keeping track of user histories. It eliminates the need for developers to build custom state and database connectors. A main difference is Julep's focus on durable execution and stateful sessions. Workflows are designed as composable dataflows that can automatically retry and resume if they crash mid-task. The platform provides SDKs for Python and Node.js, and integrates with over 100 third-party APIs. Developers can use the open-source library locally or deploy on Julep's managed cloud. For FutureStack, Julep belongs in AI Agents because its core capability is managing long-term memory, state, and orchestration for autonomous assistants. It is best for technical developers looking to build stateful, production-ready AI agents without writing custom state-management logic. It is not for business users seeking a visual no-code automation dashboard.

Use Cases

Shared Agent Memory

Capture important conversations, decisions, notes, and context so people and AI agents can recall them across workflows.

Cross-Tool Context

Record context in one supported AI tool and recall it from another through an MCP-based memory layer.

Team Knowledge Capture

Turn recurring decisions and working knowledge into connected memory that stays useful as teams collaborate.

Personal AI Context

Maintain a private, evolving knowledge base of notes, preferences, and context that can be reused across AI workflows.

Key Features

Stateful session memory that persists context across interactions
Durable workflow execution that handles automatic retries and loops
SDK support for Python and Node.js with type-safe APIs
Integrations with over 100 external application APIs

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