# put·here

put·here is a local-first spatial knowledge workbench for Mac users, built to organize material scattered across web pages, notes, screenshots, images, and folders. It places content on a freely arrangeable canvas; cards, groups, and links help you structure ideas, with optional AI search, summarization, and research. Core features — Spatial material canvas: drag text, links, images, PDFs, and files onto the canvas and place them freely so relationships are obvious. Cards and real file management: text is saved as Markdown; images and files keep their original formats; each canvas maps to a local Finder folder for backup and migration. AI organize and semantic search: AI can read the canvas, auto-group, summarize, and brief, and search across canvases by meaning. Sourced AI research: hand a question card to AI; it reads existing material, searches the web, organizes findings in a separate workspace, and keeps citations. Multiple model hooks: built-in AI, or connect DeepSeek, OpenAI, Claude, Kimi, Zhipu GLM, Tongyi Qianwen, OpenRouter, or local Ollama. Local-first privacy: no account required, no cloud sync; use built-in AI, your own API key, or fully local models.

put·here is a local-first spatial knowledge workbench for Mac users, built to organize material scattered across web pages, notes, screenshots, images, and folders. It places content on a freely arrangeable canvas; cards, groups, and links help you structure ideas, with optional AI search, summarization, and research. Core features — Spatial material canvas: drag text, links, images, PDFs, and files onto the canvas and place them freely so relationships are obvious. Cards and real file management: text is saved as Markdown; images and files keep their original formats; each canvas maps to a local Finder folder for backup and migration. AI organize and semantic search: AI can read the canvas, auto-group, summarize, and brief, and search across canvases by meaning. Sourced AI research: hand a question card to AI; it reads existing material, searches the web, organizes findings in a separate workspace, and keeps citations. Multiple model hooks: built-in AI, or connect DeepSeek, OpenAI, Claude, Kimi, Zhipu GLM, Tongyi Qianwen, OpenRouter, or local Ollama. Local-first privacy: no account required, no cloud sync; use built-in AI, your own API key, or fully local models.

Canonical: https://uniquebase.ai/products/put-here
Stable identifier: UB-D6505
Snapshot captured: 2026-10-28T00:47:51.550Z
English updated: 2026-10-28T00:56:10.070Z

## Connected profiles

- [put·here](/companies/put-here)

## Sources

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