Memori

Memori

Memori by Memori Labs provides an LLM-agnostic layer that converts agent execution and conversation into structured, persistent state, enabling reliable production systems.

LLM-agnosticpersistent stateagent executionproduction systemsmemory management
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What is Memori?

Memori is an LLM-agnostic memory layer that automatically captures, classifies, and retrieves structured context from agent conversations. It turns each chat turn into facts, preferences, rules, and summaries, giving teams full control over what's stored, how long it's kept, and where it lives. Developers use it to build reliable production AI systems without managing extra services, reducing token costs while maintaining high accuracy.

Application scenarios

  • Customer support agents

    Automatically remember user preferences and past issues across sessions to provide consistent, personalized responses.

  • Personal AI assistants

    Track facts, rules, and summaries from ongoing conversations to maintain coherent long-term interactions.

  • Research and analytics

    Use targeted recall to pull relevant context from multiple conversations and documents without manual filtering.

  • Enterprise knowledge management

    Store and retrieve structured memories with explainable lineage, tracing relevance by entity, time, and source.

  • Multi-turn agent workflows

    Reduce LLM token usage by 95% while keeping 81.95% accuracy, as benchmarked on the LoCoMo dataset.

Core Features

  • Automatic memory classification

    Captures each chat turn and categorizes it into facts, preferences, rules, and summaries, with user-defined storage controls.

  • Targeted recall

    When a prompt needs context, Memori pulls only what's relevant across conversations and documents, with no extra services to manage.

  • Selective semantic search

    Enriches searches with semantic context when language is fuzzy, improving accuracy without ballooning token costs.

  • Explainable results and lineage

    Every result includes a clear "why this was included," allowing teams to trace relevance by entity, time, and source.

  • Memory graph

    Visualizes how relationships between people, places, interests, and experiences connect and evolve across the memory network in an interactive graph.

  • Analytics dashboard

    Tracks memory creation, recall usage, and cache hit rate so you always know how the memory layer is performing.

  • One-line SDK integration

    Drop the SDK into existing code, and it handles model calls and callbacks with zero configuration.

  • Memori Cloud

    Enables instant storage and search of memories with no additional setup.

Target users

This tool is built for AI engineers, agent developers, and enterprise teams building production systems that need persistent, structured memory. It's also useful for product managers and data analysts who need to track memory performance and lineage across deployments.

How to use Memori?

Start by dropping the Memori SDK into your existing codebase with one line of code—it handles model calls and callbacks automatically with zero configuration. For instant storage and search, use Memori Cloud with no additional setup. The memory graph and analytics dashboard are available out of the box to monitor how memories connect and perform.

Effect review

Memori delivers on its promise of cutting LLM costs by over 95% while maintaining 81.95% accuracy on the LoCoMo benchmark—a strong trade-off for production systems. The automatic classification into facts, preferences, rules, and summaries is practical, and the explainable lineage gives teams confidence in what's being retrieved. The memory graph and analytics provide useful visibility into how the memory layer evolves over time. For teams building reliable AI agents that need persistent context without managing extra infrastructure, Memori offers a clean, well-tested solution.

Frequently Asked Questions

What is Memori?
Memori is an LLM-agnostic layer that converts agent execution and conversation into structured, persistent state, enabling reliable production systems.
How does Memori ensure reliability in production?
By providing a persistent state layer, Memori captures and structures agent interactions, allowing for consistent and recoverable execution.
Is Memori compatible with any LLM?
Yes, Memori is LLM-agnostic, meaning it works with any language model without requiring modifications.
What problem does Memori solve?
It solves the challenge of managing agent state and conversation history in production, which is often unstructured and unreliable.
Can Memori be integrated with existing systems?
Yes, Memori is designed as a layer that can be integrated into existing agent workflows and production pipelines.

Memori - AI Tool Detail

Memori by Memori Labs provides an LLM-agnostic layer that converts agent execution and conversation into structured, persistent state, enabling reliable production systems.

Category：Agents

Visit Link：https://memorilabs.ai/

Tags：LLM-agnostic、persistent state、agent execution、production systems、memory management