Mem0

AI agents that remember every customer, every conversation, every preference

Most chatbots forget customers the moment a session ends. With Mem0, your AI agent builds persistent memory across conversations. It recalls preferences, past issues, and purchase history, delivering personalized support that improves with every interaction.

Chosen by 800+ global brands across industries

Persistent memory for smarter conversations

Your agent stores and retrieves user-specific memories through Mem0, turning every conversation into context for the next one.

Mem0

Use Cases

Personalization that deepens with every chat

Real scenarios where persistent AI memory transforms anonymous interactions into relationships that grow stronger over time.

Remembering Customer Preferences Across Sessions

A customer who always orders medium roast, whole bean, with expedited shipping returns to your site. Your AI Agent queries Mem0 for their user profile, retrieves their stored preferences, and greets them with 'Welcome back! Shall I reorder your usual medium roast, whole bean with express delivery?' The customer feels recognized. Your repeat purchase rate climbs.

Picking Up Where the Last Conversation Left Off

A customer messaged last week about a billing discrepancy that required manager approval. They return asking for an update. Your AI Agent searches Mem0 semantically for 'billing issue' under their user ID, finds the stored context, and responds with the resolution status. No 'Can you explain your issue again?' moments. Frustration eliminated.

Building Customer Intelligence Over Months

Over six months of conversations, your AI Agent has stored dozens of memory records for a B2B customer in Mem0, tracking their growth from a starter plan to enterprise needs. When their account manager prepares for a renewal call, the agent exports all memories filtered by this customer. The manager walks in knowing every pain point discussed, feature requested, and compliment given.

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FAQs

Frequently Asked Questions

How does Mem0's semantic search work when the agent looks up past conversations?

Mem0 uses embeddings-based semantic search rather than keyword matching. When a customer asks about something discussed previously, the agent sends a natural language query to Mem0. The system finds memories with similar meaning, even if the exact words differ. This means asking about 'delivery problems' will surface memories about 'shipping delays' too.

Can the agent store memories for individual customers without mixing them up?

Yes. Every memory in Mem0 is associated with a unique user_id. The agent assigns each customer a persistent identifier, ensuring their memories are completely isolated. When Customer A returns, the agent only retrieves Customer A's memories. There is no cross-contamination between user profiles.

What kind of data does the agent store in Mem0 after a conversation?

You control what gets saved. The agent can store conversation summaries, extracted preferences, product interests, support issue details, or any structured information you configure. Mem0 supports both inferred memories (AI extracts key points) and direct storage of raw messages.

Does Mem0 retain my customer data permanently, or can I control retention?

You have full control. Memories can be deleted individually by ID, in bulk using filters, or for an entire user entity. The agent can also be configured to clean up memories after a set period. For compliance needs, you can delete all memories associated with a specific customer instantly.

How is this different from just using a CRM to track customer interactions?

CRMs store structured records that humans fill in. Mem0 gives your AI agent its own memory layer that it reads and writes to automatically during conversations. The agent recalls context mid-conversation at machine speed, personalizing responses in real-time. No human needs to log anything, and retrieval is semantic, not field-based.

Can I organize memories by project for different business units?

Yes. Mem0 supports organizations and projects. You can create separate projects within your organization, each with its own memory scope. The agent filters memories by project_id, so your e-commerce support memories stay separate from your B2B sales memories.

What happens if Mem0's API is slow during a live conversation?

Mem0 reports 91% faster response times compared to full-context approaches. But if latency occurs, the agent continues the conversation while memory lookups complete in the background. Customers never experience a delay, the personalization just enhances responses when available.

Can multiple AI agents share the same Mem0 memory for a customer?

Yes. Memories are stored at the user level, not the agent level. If you run separate agents for sales and support, both can read and write to the same customer's Mem0 profile. The support agent knows what the sales agent discussed, and vice versa, creating unified customer understanding.

How to add Tools to your AI Agent

Supercharge your AI Agent with Tool Integrations

Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.

Privacy & Security

We’ll never let you lose sleep over privacy and security concerns

At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.

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