At a critical juncture where AI technology is transitioning from perceptual intelligence to cognitive intelligence, AI infrastructure is undergoing a paradigm shift. On February 9, 2026, Zhibian Technology officially launched its multi-modal memory platform called MemoryLake, which has the capability of large-scale practical application, marking the official entry of AI infrastructure into a new era centered on "memory" rather than "data".

Why do we need a 'Memory Lake' instead of a 'Database'? Currently, enterprise-level AI applications face a core contradiction: while large models have strong generative capabilities, they often struggle to provide continuous, accurate, and explainable decisions in complex business scenarios. According to Zhan Chaoqun, CEO of Zhibian Technology, the root cause lies in existing systems being built around "data recording," whereas a true intelligent agent network (Agent Network) requires a memory computing system that processes "decision trajectories".

The Three Core Components of MemoryLake: To streamline the entire process of memory extraction, storage, and management, the platform integrates three key technologies:

MemoryLake-D1 Large Model: The first model in the industry focusing on multi-modal "memory" understanding, capable of accurately analyzing complex Excel, PDF, and audio-visual data, transforming it into structured "memory units".

MemoryLake Memory Engine: The platform's "brain," simulating human memory management mechanisms, supporting concept association, timeline backtracking, and intelligent conflict merging, significantly reducing computational costs by over 90%.

Multi-modal Data Platform (Relyt): As a persistent foundation, this platform has managed over 10 trillion records in production environments, maintaining millisecond-level retrieval latency even with massive memory databases.

From game NPCs to enterprise decision-making, memory gives AI a soul. The application of MemoryLake is reshaping multiple industry scenarios:

Enterprise Decision-Making: Compressing the originally weeks-long manual workflow into hours, and providing recommendations with complete evidence chains.

Dynamic Interaction: Building a continuously evolving "worldview memory" for game NPCs, achieving truly personalized interactions tailored for each individual.

Finance and Manufacturing: Achieving real-time risk assessment and second-level quality issue localization by integrating cross-timeline "transaction memories" or "manufacturing memories".

Currently, MemoryLake has served more than 1.5 million professional users and 15,000 enterprise customers worldwide. As AI infrastructure shifts towards "memory-driven," a cognitive computing era capable of self-evolution and deep business understanding has officially begun.