openclaw-memory-maxSOTA Memory Suite — auto-recall, cross-encoder reranking, multi-hop deep search, causal knowledge graph, episodic memory, and nightly sleep-cycle consolidation.
Install via ClawdBot CLI:
clawdbot install stanistolberg/openclaw-memory-maxGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/stanistolberg/openclaw-memory-maxAudited Apr 17, 2026 · audit v1.0
Generated Mar 22, 2026
An IT support agent uses the memory system to recall past incidents and solutions, automatically injecting relevant memories before each interaction. The agent logs successful fixes with memory_graph_add and queries past experiences before attempting complex repairs, improving resolution times and accuracy.
A customer service chatbot leverages auto-recall to remember user preferences and past issues, providing personalized responses. It uses deep_memory_search for complex queries about order history and penalizes irrelevant memories to reduce errors, enhancing customer satisfaction.
A developer assistant uses precision_memory_search to find specific configuration errors from past projects and logs causal chains with memory_graph_add after fixes. It checks memory_graph_query before deploying code to avoid known failures, streamlining the debugging process.
A medical AI assistant employs deep_memory_search to analyze patient history across multiple visits and uses auto-capture to log critical symptoms. It rewards useful memories for accurate diagnoses and consults memory_graph_summary at session start for an overview of past cases.
A financial advisor AI uses the memory system to recall client investment preferences and past market analyses. It applies reward_memory_utility for successful recommendations and queries causal knowledge before major decisions, ensuring compliance and personalized advice.
Offer the memory system as a cloud-based service with tiered pricing based on usage and features like auto-recall and deep search. Revenue comes from monthly subscriptions, targeting businesses needing enhanced AI memory capabilities for customer support or internal tools.
Sell perpetual licenses or annual contracts to large organizations for on-premise deployment, including custom integration and support. Revenue is generated through upfront fees and maintenance contracts, focusing on industries with high data sensitivity like healthcare or finance.
Provide a free version with basic memory features like auto-recall, then charge for advanced tools such as deep_memory_search and memory_graph_add. Revenue comes from upgrades and add-ons, appealing to startups and individual developers looking to scale.
💬 Integration Tip
Start by enabling auto-recall and gradually incorporate tools like memory_graph_add for logging, ensuring users train the system with reward and penalize calls to optimize memory relevance.
Scored Jun 19, 2026
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