Claude vs Onyx

Claude is an AI assistant built by Anthropic to help users with work. It is available on web, Android, iOS, macOS, Windows, Linux, through an API and as an extension. Claude can search the web, accept file uploads, create and edit spreadsheets, presentations, Word documents and PDFs, and analyze data using code execution. It can also create and share documents, dashboards, diagrams and interactive tools as artifacts; artifact storage is limited to 20 MB and text only. Connectors can link Claude with services including Asana, Linear, Notion, PayPal, Square, Plaid, Intercom, Zapier and Workato. Research, available on paid plans, runs multiple searches and returns answers with citations. Usage limits reset on a rolling five-hour window, and paid plans have additional weekly limits; usage also varies by conversation length, model and features. The Free plan includes limited usage and up to five projects. Pro costs $20 a month or $17 a year, billed $200 up front. Team plans add central billing and administration; Enterprise includes further access controls.

Onyx connects enterprise knowledge so people and AI agents can use relevant context in answers. It searches indexed sources in parallel and presents documents while enforcing each source's permissions. More than 50 connectors sync connected tools in the background and support hybrid semantic and keyword search. The Business plan lists chat and search, major LLM access, custom agents, MCP/OpenAPI actions, web search, deep research, code interpreter, and image generation. Business costs $20 a month, billed annually at $20 per user per month, for teams of any size, with 40+ app connectors and Community Support. Onyx provides APIs for messages, agents, LLM management, actions, and user authentication. Slack integrations can provide responses and agents; Microsoft Teams and Zendesk are described as coming soon. Deployments can run in a customer's cloud or on bare metal, including on-premise and fully air-gapped environments. The site says documents and embeddings can remain in customer infrastructure, data is not used for training, and permissions are checked at query time. Native Windows, macOS, and Linux apps connect to an existing deployment.