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Related Products
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Activeloop:
About
Activeloop provides a continuous learning infrastructure for teams building software, agents, and data pipelines. Its core product, Deeplake, is the GPU database for agents, built around the idea that if your AI is on a GPU, your data should be too. Deeplake is designed to keep AI agents grounded, versioned, queryable, and GPU-native by combining vector and tensor data in one store, with GPU streaming to fine-tuning and a serverless Postgres interface. It gives teams a data engine for multimodal AI, allowing them to store, index, search, and stream data to models and agents. Instead of treating AI data as scattered files, embeddings, metadata, and traces across disconnected systems, Activeloop brings them into an infrastructure that can support retrieval, model development, fine-tuning, and agent memory workflows. It also includes Hivemind, where agent traces become team skills, so work solved once can be shared across the organization through trajectory capture.
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tensorViz:
About
tensorViz helps developers explore PyTorch models and JAX/Flax programs as interactive graphs. For PyTorch, users can expand nested modules, inspect tensor shapes captured from one forward pass, jump to Python source, and review architecture changes beside code diffs. The website offers recorded model graphs to explore without installation. The free VS Code extension is available from the Visual Studio Marketplace and Open VSX. Local capture requires Python, model dependencies, and example inputs. Standalone coding-agent plugins are an Apple Silicon macOS preview; MCP agents can also connect to the extension. JAX/Flax graphs use CPU tracing with inferred shapes, and PyTorch source edits are unavailable for them.
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Activeloop:
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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tensorViz:
Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Activeloop:
Audience
Software building teams that need GPU-native data, memory, and continuous learning systems for multimodal AI applications
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tensorViz:
Audience
Machine learning engineers, PyTorch developers, researchers and students exploring model architecture, tensor shapes and architecture changes.
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Activeloop:
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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tensorViz:
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Activeloop:
API
Offers API
Not Supported
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tensorViz:
API
Offers API
Supported
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Activeloop:
Screenshots and Videos |
tensorViz:
Screenshots and VideosNo images available
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Activeloop:
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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tensorViz:
Pricing
$0
The VS Code extension is free to install. Core graph exploration and source-edit forms work without an agent or provider API key; connecting a coding agent is optional.
Free Version
Supported
Free Trial
Not Supported
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Activeloop:
Reviews/
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tensorViz:
Reviews/
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Activeloop:
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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tensorViz:
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Activeloop:
Company InformationActiveloop
Founded: 2018
United States
www.activeloop.ai/
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tensorViz:
Company InformationtensorViz
tensorviz.dev/
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Activeloop:
Alternatives |
tensorViz:
Alternatives |
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tensorViz:
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Activeloop:
Categories |
tensorViz:
Categories |
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Activeloop:
Integrations
Claude Code
Not Supported
Codex CLI
Not Supported
Cursor
Not Supported
Deeplake
Supported
GitHub
Not Supported
Model Context Protocol (MCP)
Not Supported
T3 Code
Not Supported
Visual Studio Code
Not Supported
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tensorViz:
Integrations
Claude Code
Supported
Codex CLI
Supported
Cursor
Supported
Deeplake
Not Supported
GitHub
Supported
Model Context Protocol (MCP)
Supported
T3 Code
Supported
Visual Studio Code
Supported
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Activeloop:
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tensorViz:
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