Agents That Remember
Your AI agents forget everything after every conversation. Ours don't. A 5-layer persistent memory hierarchy that gives your agents institutional knowledge.
The Problem
Stateless agents are a dead end
Every conversation starts from zero. Every workflow forgets its history. Every new agent has no institutional context. Your AI is building on sand.
Lost context
Customers repeat themselves every conversation. Context windows are a band-aid, not a solution.
No learning
Workflows make the same mistakes. There is no feedback loop from execution history to future runs.
Zero onboarding
Every new agent starts from scratch. No awareness of department processes, preferences, or accumulated wisdom.
5-Layer Memory
Memory that mirrors how organizations think
Five layers of persistent memory, from individual entities to cross-workflow insights. Each layer builds on the one below.
Entity Memory
Persistent facts about customers, products, and projects. Your AI remembers every interaction across all departments.
A customer mentions their Q3 budget constraints in January. In March, a different agent in a different workflow automatically adjusts its proposal.
Workflow Memory
Per-workflow accumulated knowledge from execution history. Your workflows learn from every run and improve automatically.
Your invoice processing workflow has run 500 times. It now knows that supplier X always sends PDFs with non-standard headers and auto-adjusts.
Department Memory
CLAUDE.md-equivalent per department. New team members, human or AI, onboard instantly with department knowledge.
A new marketing agent is created. It instantly knows the brand voice, campaign history, and audience segments without manual configuration.
Agent Memory
Each agent retains context across conversations and tasks. Persistent state that survives session boundaries.
A support agent remembers a customer from a conversation 3 months ago and picks up where they left off.
Cross-Workflow Memory
Insights from one workflow automatically inform others. Entity memory shared across all workflows in a department.
Sales discovers a customer is evaluating a competitor. Support, marketing, and account management workflows all gain that context automatically.
Comparison
How JieGou memory compares
Competitors offer point solutions. JieGou offers a hierarchy.
| Capability | JieGou | LangGraph | CrewAI | n8n | Vertex AI |
|---|---|---|---|---|---|
| Memory layers | 5 | 1 | 1 | 1 | 2 |
| Entity-level memory | Yes | No | No | No | Partial |
| LLM compaction | Yes | No | No | No | No |
| Department-level memory | Yes | No | No | No | No |
| Cross-workflow sharing | Yes | No | No | No | Partial |
| Governance integration | Yes | No | No | No | No |
LLM Compaction
Memory that grows, not overflows
As entities accumulate interactions, LLM compaction automatically summarizes older memories into concise, high-signal context. Memory stays relevant without unbounded growth.
entries trigger compaction
intelligent summarization
interaction history, bounded storage
Use Cases
Memory-powered workflows in action
Customer Support
Your support agent remembers every customer interaction. Previous issues, preferences, and context are available instantly. No more "Can you explain the issue again?"
Marketing Campaigns
Workflows learn from every campaign execution. Content that performed well, audience segments that converted, messaging that fell flat. Each run gets smarter.
Financial Compliance
Department memory stores audit requirements, budget thresholds, and approval workflows. Every agent in Finance operates with full compliance context from day one.
Give your agents institutional memory
Start with a free trial and see how persistent memory transforms your AI workflows.