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.
