Shared State Context for AI Agents [Ask/Show][Looking for Beta]

1作者: aperi30 天前原帖
Hola Hackers!<p>I&#x27;m building Rice (docs.tryrice.com). Think of Rice as a managed state machine for AI agents with long term memory.<p>Rice is a platform that unifies long term memory and short term state management for AI agents. Effectively, Rice solves the context compounding issue in the immediate sense - by using Rice Slate (our state management service), the context consumption was down 60%. This makes the agents more efficient. The state management layer also allows agents to share context without the conventional &quot;message passing&quot; approach meaning you can run parallel AI agents.<p>The memory layer enables the agents to have a broader contextual understand of the data and relationships - personalisation and automation at scale for agents.<p>How we&#x27;re different (https:&#x2F;&#x2F;docs.tryrice.com&#x2F;rice-vs) and working on some cool aspects.<p>The core value prop -<p>1. Auditable Agentic executions out of the box 2. Shared state for AI agents (not using message passing approach) for efficient executions 3. Persistent memory for historical data and more.<p>Currently in beta phase, so looking for beta testers. Appreciate any thoughts and tests.<p>Please enter your email at tryrice.com if you&#x27;d like to get in the beta.
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Hola Hackers!<p>I&#x27;m building Rice (docs.tryrice.com). Think of Rice as a managed state machine for AI agents with long term memory.<p>Rice is a platform that unifies long term memory and short term state management for AI agents. Effectively, Rice solves the context compounding issue in the immediate sense - by using Rice Slate (our state management service), the context consumption was down 60%. This makes the agents more efficient. The state management layer also allows agents to share context without the conventional &quot;message passing&quot; approach meaning you can run parallel AI agents.<p>The memory layer enables the agents to have a broader contextual understand of the data and relationships - personalisation and automation at scale for agents.<p>How we&#x27;re different (https:&#x2F;&#x2F;docs.tryrice.com&#x2F;rice-vs) and working on some cool aspects.<p>The core value prop -<p>1. Auditable Agentic executions out of the box 2. Shared state for AI agents (not using message passing approach) for efficient executions 3. Persistent memory for historical data and more.<p>Currently in beta phase, so looking for beta testers. Appreciate any thoughts and tests.<p>Please enter your email at tryrice.com if you&#x27;d like to get in the beta.