Next Moca

A context relevance engine that selects the most relevant parts of AI agent state before each model call, reducing input tokens and improving answer quality. It targets developers and engineering teams building AI agents, especially those dealing with large context windows. It differentiates by selecting original content in milliseconds without rewriting, and it can hand over the full context when needed.

Key features

• Selects relevant context in milliseconds
• Reduces input tokens by 32.7%
• Improves answer quality by 4.62 pp
• No second model in the loop
• Handles full context when needed
• Preserves exact details in forms
• Benchmarked on public tests