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NOTE: Agent Memory is currently in Beta, and some features aren’t available yet, but are clearly marked with a ‘Coming Soon’ label.

What is Agent Memory?

Agent Memory helps your AI agents remember important details about the people they work with. Instead of starting every conversation from scratch, your AI can remember that Sarah likes quick updates, John’s team is preparing for the Q4 launch, or that the marketing team prefers longer explanations. Think of it as giving your AI agents the ability to build relationships and provide more personalized help over time.

Build Better Relationships

Your AI agents can create genuine connections by remembering context and personalizing interactions.

Stop Repeating Yourself

No more answering the same questions every time you talk to your AI agent.

Work More Efficiently

Get more relevant, helpful responses that save you time.

Stay Compliant

Built-in protection for data privacy that meets global standards.
The key point: Agent Memory turns your AI agents from basic tools into truly intelligent helpers that understand your context.

How Agent Memory Works: Three Levels of Control

Agent Memory uses a three-layer system that gives you complete control over how your organization uses AI memory.
  • Layer 1: Organization Policy
  • Layer 2: Agent-Specific Configuration
  • Layer 3: Individual Control
Global Agent Configuration - Set your company-wide memory policyMaster Switch: Enable or disable memory collection across your entire organizationPolicy Guidance: Define what types of information align with your business goals. For example, “Do not store address information”.Consistency: Ensure all agents follow the same organizational principles
This layer establishes your organization’s “memory philosophy” and ensures consistent policies across all AI deployments.

What Gets Remembered

Agent Memory intelligently categorizes information into meaningful groups:

Professional Context

Job roles, team relationships, project involvement

Communication Preferences

Meeting styles, information formats

Work Patterns

Availability, deadlines, collaboration styles

Goals & Objectives

Project priorities, professional development
Each fact includes full context: which conversation it came from, which agent collected it, and when.

Administrative Tools

Human Facts Management

Navigate to any individual’s Human Facts tab to access:
Central dashboard showing all collected information, sortable and searchable (Coming Soon)
Modify any fact while maintaining complete audit trails (Coming Soon)
One-click exports in CSV format for compliance reporting
Select multiple facts for batch operations (Coming Soon)Currently we can delete all of a user’s facts via bulk operations

Compliance Features

Automatic Legal Framework Support:
  • EU AI Act (2024): 6+ month logging retention and decision transparency
  • GDPR: 30-day response automation for all data subject rights (Articles 15-22)
  • CCPA/CPRA: 45-day processing with comprehensive deletion capabilities
  • US State Laws: Virginia, Colorado, Connecticut, Utah coverage
  • PIPEDA: Full accountability and access rights implementation
Built-In Data Rights:
  • Right to Access: Instant visibility of all collected facts
  • Right to Rectification: Direct editing with full audit trails (Coming Soon)
  • Right to Erasure: Complete deletion with verification across all systems
  • Right to Portability: Professional data exports with metadata

Real Examples of How Agent Memory Works

🎧 Customer Support Excellence

Your customer support AI talks to Sarah, who calls monthly about her software setup. Without memory, every call starts over. With memory, the AI agent immediately knows:
  • Her technical setup details
  • She prefers brief, technical explanations
  • Her team’s current project
Setup: Enable both reading and writing memory, with guidance focusing on technical preferences and solution history.

📊 Project Management Help

Your project management AI works with multiple teams. Memory helps it remember:
  • Who does what on each team
  • Project deadlines and dependencies
  • Context across different project phases
Setup: Full memory abilities with guidance emphasizing project context, deadlines, and team relationships.

🔒 HR Conversations

Your HR AI handles sensitive discussions. You might set it up to:
Without storing new sensitive information
To prevent storing confidential details
About appropriate workplace context
Setup: Reading enabled, writing disabled, with very specific guidance about appropriate context.

Getting Started

Set Your Foundation

Start with your organization’s memory policy. Go to Global Agent Configuration and establish guidelines about what information would genuinely help your AI agents provide better service.

Try It Out

Choose 1-2 AI agents for initial testing. Customer support and project management agents often show immediate value. Enable both _reading _and contributing with specific guidance about what to remember.

Watch and Improve

Monitor how your AI agents use memory over the first few weeks. Are they collecting useful information? Are users finding conversations more helpful? Use the Human Facts tab to review what’s being learned.

Expand

Based on your trial results, add memory to more AI agents. Each type may need different guidance - your sales agents focus on different information than your technical support agents.
Pro Tip: Start with AI agents that have frequent repeat conversations - they’ll show the most immediate value from remembering context.

Common Questions

  • Setup Questions
  • Privacy Questions
  • Troubleshooting
Look for these signs: Users stop repeating basic information, AI agents give more relevant responses, and you see fewer “starting from scratch” conversations. The Human Facts tab will show growing, useful information over time. An admin would know that memory is working on a specific agent if they tell the agent a fact in the Preview tab and the 💡 fact status update shows
Reading means the AI can use existing information about someone. Contributing means the AI can learn and store new information. You might have some AI agents that only read context, and others that focus on learning new information.
Be as specific as helpful. Instead of “remember user preferences,” try “remember preferred communication style (email vs. phone), typical project deadlines, and team collaboration preferences.”
Agent Memory transforms transactional AI interactions into intelligent, evolving relationships while maintaining the highest standards of data protection and regulatory compliance.