1. Overview

Features of Sila

Workspaces

Organize your chats and assistants into separate workspaces. Each workspace can have its own assistants, files, themes, and languages. Create multiple workspaces for different purposes and switch between them quickly.

Workspaces in Sila

Files and folders

Attach files to chats and reuse them across your workspace. Organize your assets into folders. Sila has its own virtual file system.

Filees and folders in Sila

Documents

Assistants can write and edit text documents (in Markdown) locally inside a chat and save them to workspace folders so they can be referenced in other conversations.

Document editing and viewing in Sila

Flexible chats

When you chat, you can switch between assistants, branch conversations, reference files from across the workspace, and edit messages created by you or the AI.

Chats in Sila

Assistants

Create your own assistants with their instructions, AI models, and tools. Assistants can support different workflows. For example, an assistant can always search a specific source, reference a document, and create conversations in a chosen project.

Assistants in Sila

Local-first

Workspaces are stored locally. You can sync them with iCloud, Dropbox, or similar services to use across devices. Your assistants, chats, and generated data remain under your control. Sync conflicts are resolved automatically. No accounts required. Sila works offline if the AI model runs on your device.

Tabs like in VSCode

Switch between tabs and split windows. It works much like VS Code. You can have multiple conversations open across tabs, chat with different assistants at the same time, and quickly switch between them.

Tabs like in VSCode

Many themes

Use different themes for your workspaces—from colorful to minimal. It's a simple way to set a mood or tell your workspaces apart.

Themes in Sila

Any AI models

You can use any major AI model from the ones powering ChatGPT, to Claude and Gemini.

AI providers in Sila

No subscriptions

Pay as you go for provider API costs or local compute if you run models yourself.