What is Canto?

Canto is a private AI notebook for macOS that runs AI models locally and stores notes in an encrypted SQLite database.It provides an interactive knowledge graph and memory links that map notes, notebooks, tags and folders for semantic navigation.

Semantic search, autocomplete and selection-based AI actions surface related content across large vaults and support multi-step agent workflows that edit notes with diff review and approval.Code notebooks support Python, JavaScript and TypeScript with Jupyter-style cells and local code execution for prototyping and reproducible analysis.

PDF import and integrated web research let users extract, summarize and cross-reference sources without uploading data to the cloud.Model selection and Metal GPU acceleration support configurations from small models (~1.9 GB) to large models (up to 80B) and MOE contexts (32k–262k), with split panes and tab cycling for multitasking.All AI inference runs locally with no cloud uploads and encrypted storage, supporting privacy-sensitive workflows for researchers, writers, developers and knowledge workers on Apple Silicon Macs.

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Canto's key features

Local AI inference and model selection with Metal GPU acceleration and encrypted SQLite storage (no cloud uploads)
Interactive knowledge graph and memory links mapping notes, notebooks, tags and folders for semantic navigation
Semantic search, autocomplete and selection-based AI actions with multi-step agent workflows and diff-reviewable edits
Code notebooks with Jupyter-style cells supporting Python, JavaScript and TypeScript and local code execution
PDF import and integrated web research for extracting, summarizing and cross-referencing sources locally

Canto use cases

Create an encrypted, searchable research wiki from PDFs and clipped web pages using Canto's PDF import and semantic knowledge graph, automatically generate concise summaries and citations with on-device models, and keep all notes private in encrypted SQLite storage on your Mac
develop reproducible data-processing pipelines and experimental notebooks using Canto's code cells (Python/JavaScript/TypeScript), run and iterate models locally with Metal-accelerated inference, capture results and links in the semantic knowledge graph for easy reuse and collaboration offline
Create a private on-device knowledge assistant for sensitive company data by ingesting internal PDFs and research, use selection-based AI actions and semantic search to produce briefings, action items, or code snippets, and ensure everything stays local and encrypted for compliance