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Home/Categories/AI & Machine Learning/Orkas
icon of Orkas

Orkas

  • 6.2K stars
  • MIT
  • Active this week
  • Last commit 1 day ago

Last verified Nov 1, 2026

Run a team of 16 specialist AI agents on your desktop; the Commander delegates work while your files, keys, and memory stay local.

Visit websiteGitHub6.2K stars
image of Orkas
TL;DR

Orkas is a local-first desktop app that puts a Commander-led team of 16 AI specialists on your machine, delivering finished work on research, content, code, and business tasks rather than chat responses. For solo founders and small teams, it replaces a mix of paid SaaS subscriptions and standalone models with one workspace where agents and people share projects, memory, and to-dos. MIT licensed, free to download for macOS and Windows, with all data on your own machine by default.

Read the full breakdownHide the full breakdownWho it is for, how it works, trade-offs, the quick start and the FAQ
who it's for

Who Orkas is for#

Solo founders running recurring business operations

Orkas handles weekly sales briefs, content drafts, and client reports on a schedule. Set up automations once in a project that carries your brand voice, product facts, and preferences, and agents deliver formatted outputs for your review every time without re-briefing.

Skip if:

If you only need a single ad-hoc task occasionally, the project setup and scheduling overhead is more than a one-shot conversation with a standalone model.

Small marketing teams producing content cycles

ContentWriter, ImageStudio, and VideoStudio share a project's memory of your brand voice and previous content, so weekly posts, product launch kits, and newsletters stay consistent. Output files including video and PowerPoint decks come back as reviewable deliverables before publication.

Skip if:

Teams that need AI assistance for only one step, such as caption writing, will get faster results from a direct API call than from setting up a full multi-agent project.

Developers integrating coding agents into a wider workflow

Orkas runs Claude Code, Codex, OpenCode, OpenClaw, and Hermes-Agent as part of the same Commander-directed project alongside research and content specialists. A single instruction can fix a bug, write the changelog entry, and draft the release announcement in sequence.

Skip if:

If the work is purely coding and you are satisfied with Claude Code or Codex in your terminal or IDE, adding a multi-agent coordination layer is unnecessary overhead.

E-commerce operators managing store workflows

Five dedicated e-commerce agents handle product research, listing writing, review analysis, sales analysis, and catalog operations. Weekly briefs can be scheduled as automations, with review reply drafts queued for your approval before any action is taken on a connected store.

Skip if:

If your e-commerce tool already provides native AI features for your primary workflows, evaluate whether Orkas's agent depth justifies a separate desktop tool alongside it.

the problem

The problem it solves#

Running a small business or solo practice means either paying for a growing stack of specialised SaaS tools, each with its own login, export, and data silo, or cycling through a single general-purpose chat model and manually stitching outputs together across sessions. Neither approach keeps work organized across days, runs routine tasks automatically, or lets agents and people share a live project with shared context.

The deeper pain is repetition. Weekly content cycles, monthly client reports, recurring store operations, and regular codebase maintenance all require the same setup conversation every time. A chat model with no project memory means briefing from scratch on Monday, again on Thursday, and again the following week.

how Orkas solves it

How it solves it#

Commander-led task routing

The Commander agent takes a goal, plans the steps, and assigns each part to the most appropriate specialist. It handles analysis, writing, research, and file work itself when no specialist is a better fit, and runs the 16 built-in specialists alongside external CLI tools like Claude Code and Codex when the task calls for it.

16 built-in specialist agents

Agents cover research (DeepResearcher), content writing (ContentWriter), video (VideoStudio), audio (VoiceStudio), slide decks (PptMaker), UI design (UIDesigner), software development (ProductDeveloper), office documents (OfficeWorker), SEO audits (SeoGeoAgent), stock analysis (StockAnalyser), and five e-commerce agents for product research, listings, reviews, sales analysis, and catalog operations.

Projects with persistent memory

A project holds the goal, rules, memory, and files for a business or workflow. Every conversation picks up from the last, so agents carry your brand voice, product facts, and preferences without re-briefing. Memory is stored locally and can be reviewed or edited at any time in the Memory panel.

Scheduled automations

Any task can run on a repeat schedule: hourly, daily, weekly, or monthly. Automations run on your machine, and since version 1.9, each automation catches up its most recent missed run within 12 hours when the device wakes. Recurring tasks like weekly content drafts, order reviews, or client briefs run without manual triggering.

Model and agent flexibility

Orkas uses the built-in Orkas model out of the box (500 free credits on sign-up) or connects to OpenAI, Anthropic, Google Gemini, DeepSeek, Kimi, GLM, Qwen, MiniMax, Doubao, or any local OpenAI-compatible endpoint. External CLI agents including Claude Code, Codex, OpenCode, OpenClaw, and Hermes-Agent plug in as first-class team members alongside the built-in specialists.

Local-first data storage

Files, conversations, knowledge bases, and custom agent definitions stay on your disk by default. API keys are encrypted locally and excluded from cloud sync. Cloud sync is optional in the packaged app; with your own provider keys, model calls go directly from your machine to the provider, not through Orkas servers.

strengths · trade-offs

Strengths and trade-offs#

Strengths

  • MIT license with no usage restrictionsThe full desktop app is MIT licensed, so you can read the source, fork it, and use it commercially with no restrictions. Unlike proprietary AI tools that charge per seat or restrict commercial use, there are no per-call fees for self-managed provider keys; you pay only the underlying model API cost.
  • Local-first by designConversations, files, knowledge bases, and custom agents live on your disk. API keys are encrypted locally and excluded from cloud sync. For teams handling client data, unreleased products, or financial records, the AI team never transfers sensitive files to a third-party service by default.
  • Coordinates external coding agentsOrkas runs Claude Code, Codex, OpenCode, OpenClaw, and Hermes-Agent as part of the same Commander-directed project alongside its own specialists. A single task can fix a bug via Claude Code, review the diff with a specialist agent, and draft the release post, all in sequence without manual handoffs between separate tools.
  • Any model, switchable at any timeThe Commander and all built-in agents share one model setting. Switch from the built-in Orkas model to your own OpenAI, Anthropic, Gemini, or DeepSeek key in Settings without reconfiguring each agent individually. Local OpenAI-compatible endpoints also work, letting you run models on your own hardware.

Trade-offs

  • -Cloud features require the packaged appShared projects, cloud sync, app publishing, and web-app hosting are available only in the packaged macOS or Windows app, not in the open-source build. Teams that need to invite a collaborator or share a published web app must use the packaged version rather than the source checkout.
  • -Linux requires running from sourceThere is no packaged installer for Linux. Running Orkas on Linux requires Node 22.12 or later, glibc 2.34 or higher, and a C/C++ build toolchain. Alpine and musl-based distributions are not supported. First launch downloads approximately 95 MB of assets including an embedding model, Whisper speech runtime, FFmpeg, and Python tooling.
  • -Built-in model uses Orkas-managed creditsThe built-in Orkas model runs through Orkas's cloud service, so those calls and voice transcription require an account and use credits. With 500 free credits on sign-up, light use is covered, but high-volume tasks or intensive automations will need a paid plan or a bring-your-own-provider key.
versus alternatives

Orkas vs alternatives#

Orkas vs ChatGPT

Both tools use a chat interface for AI assistance, but they serve different models of work. ChatGPT is a hosted web and mobile assistant that handles one conversation at a time with a single general model; Orkas is a local-first desktop app where a Commander routes different parts of a goal to 16 specialist agents working together.

FeatureOrkasChatGPT (Plus/Teams)
LicenseMIT open sourceProprietary
Data locationLocal by defaultOpenAI servers
Specialists16 built-in plus CommanderSingle general model
Project memoryPer-project, stored locallyLimited conversation memory
Scheduled automationsYes, hourly to monthlyNo
Model choiceAny provider or local endpointOpenAI models only
PricingFree app; bring-your-own-key billing$20/month (Plus) per seat

Orkas is the stronger choice when you need specialist output for video, research, or e-commerce work, recurring automations, or a project that carries full context across days without re-briefing. The VideoStudio, DeepResearcher, and e-commerce agents operate with dedicated tooling that a general chat model does not match for that type of work.

ChatGPT is still the right fit when you want a single conversational assistant with no local setup, when you work mostly on a mobile device, or when you need web search integrated into a one-off response.

Orkas vs Microsoft Copilot

Microsoft Copilot is embedded in Microsoft 365 and Windows, built for users who live in Word, Excel, Teams, and Outlook. It is a deep Microsoft integration, not a standalone multi-agent coordinator.

FeatureOrkasMicrosoft Copilot
LicenseMIT open sourceProprietary
Data locationLocal by defaultMicrosoft cloud
Integration targetAny tool via connectorsMicrosoft 365 apps
Agent approach16 specialists plus CommanderSingle model per Microsoft app
PricingFree app$30/user/month (M365 Copilot)

Orkas fits teams who want a model-agnostic local workflow across tools beyond Microsoft's ecosystem: Shopify, Notion, Stripe, Google Workspace, and Slack all connect, and agents work with local files without uploading them to a cloud tenant. The MIT license is an advantage if your organization audits what AI tools access your data.

Copilot is the better fit when your organization is standardized on Microsoft 365, data governance requires staying in the Microsoft cloud, and the primary use case is document summarization and email drafting inside those apps.

install · quick start

Quick start#

bash
Download the free macOS or Windows installer from GitHub Releases: https://github.com/Orkas-AI/Orkas/releases/latest
tech stack · detected from GitHub

What it's built on#

Languages
JavaScriptPythonTypeScript
Frameworks
Electron
frequently asked

FAQ#

Is Orkas free to use?

The desktop app is free to download and comes with 500 credits for the built-in Orkas model. Using your own OpenAI, Claude, Gemini, DeepSeek, or other provider keys is free from Orkas's side; you pay your provider's rates directly. Paid plans add monthly credits, multi-device sync, more shared projects, and additional cloud storage.

Does Orkas send my files or data to the cloud?

By default, files, conversations, knowledge bases, and custom agent definitions stay on your machine. API keys are encrypted locally and excluded from cloud sync. With your own provider keys, requests go directly from your device to the provider. Cloud sync is an opt-in feature in the packaged app and does not run by default.

Can Orkas run on Linux?

Linux support is via source build only; there is no packaged Linux installer. Requirements are Node 22.12 or later, glibc 2.34 or higher, and a C/C++ build toolchain. Alpine and musl-based distributions are not supported. Clone the repo and run ./run.sh; first launch downloads the embedding model, Whisper runtime, and FFmpeg automatically.

What is the difference between Orkas and a coding agent like Claude Code or Codex?

Claude Code and Codex are coding-focused agents that work on code in your terminal or IDE. Orkas is a multi-agent coordinator: the Commander routes different parts of a goal to specialists, and Claude Code or Codex can be one of those specialists inside the same Orkas project. A single task in Orkas can fix a bug via Claude Code, draft the changelog, and create the release post all in sequence.

What model providers does Orkas support?

The built-in Orkas model is included out of the box and requires no API key to start. You can also connect OpenAI, Anthropic Claude, Google Gemini, DeepSeek, Kimi (Moonshot), GLM, Qwen, MiniMax, Doubao, and any local OpenAI-compatible endpoint. All agents share the same model setting, so switching providers applies to the whole team at once.

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