DeeplakeActiveloop
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LangMemLangChain
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Related Products
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About
Deeplake is a GPU-native database for AI agents that helps teams store, retrieve, and process data where their models already run. Built by Activeloop, it is designed as a memory and data layer for production-grade AI agents, agentic loops, physical AI, and generative media workflows. The platform combines a familiar Postgres-style interface, analytical query performance, multimodal data lake capabilities, and GPU acceleration into one AI-focused data system. Deeplake supports use cases involving text, images, video, sensors, 3D scans, model weights, embeddings, and other complex data types. It helps agents retrieve context faster, reduce data movement, and run large volumes of queries more efficiently than traditional CPU-based database architectures. With SOC 2 Type II certification, VPC deployment, open-source traction, and support for modern AI stacks, Deeplake gives AI teams a scalable foundation for agent memory, retrieval, and multimodal data management.
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About
LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Deeplake is best suited for AI engineers, machine learning teams, agent developers, robotics teams, RAG builders, data infrastructure teams, generative media companies, and enterprises that need GPU-native retrieval, multimodal data management, vector search, serverless Postgres, and scalable memory for production AI agents
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Audience
AI developers and data scientists who build LangChain-based agents and want to implement long-term, structured memory to enhance personalization, coherence, and conversational depth
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
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Pricing
$0
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationActiveloop
Founded: 2018
United States
deeplake.ai/
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Company InformationLangChain
Founded: 2022
United States
langchain-ai.github.io/langmem/
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Alternatives |
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Categories |
Categories |
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Integrations
Activeloop
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
Jupyter Notebook
LangChain
LangGraph
OpenAI
PyTorch
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Integrations
Activeloop
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
Jupyter Notebook
LangChain
LangGraph
OpenAI
PyTorch
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