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Slashspace (Formerly RabbitHoles AI)

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Introduction: Slashspace is a local-first infinite canvas for branching AI conversations, connected sources, multiple models, agents, and sustained research or knowledge work.
Added on: 2026-08-07
Monthly Visitors: 110.2K
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$5/month
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Slashspace (Formerly RabbitHoles AI) Product Information

What is Slashspace (Formerly RabbitHoles AI)?

Slashspace, formerly RabbitHoles AI, replaces a stack of disconnected chat threads with an infinite spatial canvas. Users can branch conversations from any point, arrange related work as nodes, attach PDFs, websites, YouTube videos, spreadsheets, images, and text files, and let agents work with the shared context of a space.

The desktop application supports managed models, local Ollama models, and—on eligible plans—external providers and coding agents. Because a canvas can contain proprietary files, API keys, and tool connections, users should keep sensitive projects local, grant each integration the minimum access, verify cited sources, and review agent actions before they affect files or external systems.

Research basis: This is a source-based directory listing prepared from public product information; it is not represented as a hands-on test. Last updated August 8, 2026. Read our methodology.

How to use this tool

  1. Create a separate space for one project, place the core question in the first node, and add only the files, web pages, videos, or tables needed.
  2. Branch alternative lines of inquiry instead of mixing them, label decisive nodes, and connect each claim to the evidence that supports it.
  3. Choose the model and system prompt deliberately, and compare important answers across sources or models when uncertainty could change the outcome.
  4. Before enabling provider keys, Composio, MCP, or coding agents, inspect permissions, costs, destinations, and every action that can change an external system.
  5. Verify conclusions against original sources, remove unnecessary sensitive context, and export a clean project record when the work is complete.

Core Features

  • Infinite AI-native canvas
  • Branching conversations and connected nodes
  • Shared context across agents and sources
  • PDF, web, YouTube, spreadsheet, and file inputs
  • Managed, cloud, local, and coding-agent models
  • Local-first workspace storage
  • Model and system-prompt controls
  • Workspace export and reusable context

Use Cases

#1 Map a complex research question
#2 Compare model answers without losing context
#3 Develop a long-form writing project
#4 Connect evidence to an analysis canvas
#5 Coordinate agents around one persistent workspace

Frequently Asked Questions

Slashspace (Formerly RabbitHoles AI) Support Email & Customer service contact & Refund contact etc.

More Contact, visit the contact us page.

Slashspace (Formerly RabbitHoles AI) Login

Slashspace (Formerly RabbitHoles AI) Login Link: https://www.slashspace.ai/

Slashspace (Formerly RabbitHoles AI) Sign up

Slashspace (Formerly RabbitHoles AI) Sign up Link: https://www.slashspace.ai/

Slashspace (Formerly RabbitHoles AI) Pricing

Slashspace (Formerly RabbitHoles AI) Pricing Link: https://www.slashspace.ai/pricing
Slashspace (Formerly RabbitHoles AI) Reviews
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Slashspace (Formerly RabbitHoles AI) Pricing
Starter
$5/month
For light canvas use.
  • One device, two desktop canvases, limited AI models, and $4 monthly included usage.
  • Full canvas, unlimited branches and nodes, supported sources, and local-first storage.
Pro
$49/month
For broader model access.
  • Two devices, all AI models, faster response pools, and usage reloads.
  • $30 monthly included usage.
Advanced
$99/month
For high managed usage or BYOK.
  • Two devices, all models, BYOK, faster response pools, and reloads.
  • $80 monthly included usage.
Lifetime
$129 One-time
For technical users bringing their own keys.
  • Two devices, BYOK, lifetime updates, and usage reloads.
  • $10 one-time included usage grant.
Slashspace (Formerly RabbitHoles AI) Launch embeds
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Slashspace (Formerly RabbitHoles AI)'s Tags
Agents › API › assistant › MCP › Run Locally ›