Slashspace AI

What is Slashspace AI

Slashspace is an intelligent, local-first infinite canvas designed for multi-agent AI chat and deep research. It aims to solve the problem of context collapse by allowing users to manage multiple AI conversations, tools, and data sources within a single, organized canvas.

Features of Slashspace AI

• Infinite Canvas: A spatial environment for organizing thoughts and AI interactions.
• Multi-Agent AI Chat: Supports running multiple AI conversations and agents simultaneously.
• Context Linking: Enables context sharing between different parts of the canvas.
• Local-First Storage: Data is stored locally on the user's device.
• Pluggable Intelligence: Supports various AI models and providers.
• Tool Integration: Connects to various tools and data sources.
• Configurable Prompts and Settings: Allows customization of system prompts and model settings per conversation or provider.
• Branching Conversations: Conversations can branch and share context.

Use Cases of Slashspace AI

• Founder's Desk: Investor research, competitive analysis, financial modeling, and strategy sessions.
• Development: (Details not provided in the content)
• Deep Learning: (Details not provided in the content)
• Research: (Details not provided in the content)
• Writing: (Details not provided in the content)

FAQ

• What is Slashspace? Slashspace is an AI canvas for deep work, consolidating multiple AI conversations, files, and agents with shared context into one place.
• How does Slashspace work? Each canvas is scoped to a project. Users add files, run multiple AI chats, and utilize agents that can access all canvas content. Conversations branch and share context.
• Why use Slashspace over other tools? Unlike tools built around single linear sessions and vendors, Slashspace offers a spatial canvas, pluggable intelligence (multiple AI models), and local-first data storage.
• What AI models can be used? Any model from OpenAI, Anthropic, Google, Perplexity, xAI, OpenRouter, or local models via Ollama.
• Where is data stored? Data stays on the user's device, with each canvas being a folder on the computer, unless opting for RAG indexing.
• Does it use more tokens? Not necessarily. Scoped nodes and precise context engineering can lead to fewer tokens used overall by focusing on relevant information.
• Why keep past chats? Past chats pay off over time for solving similar problems and save time by avoiding regeneration.
• What was RabbitHoles AI? RabbitHoles AI was the previous name for Slashspace; it's the same product with a new name reflecting its vision.

Pricing

• The product is offered at $89 USD.