Gab AI Research Assistant vs Onyx

Gab AI Research Assistant produces structured reports with citations from a topic and inputs such as audience, preferred source types, research depth, and focus questions. Reports can include an executive summary, findings, detailed analysis, sources, counterpoints, debate, and open questions. Users can choose Quick scan, Standard, Deep, or Exhaustive depth; report lengths range from 500 words for Quick scans to 5,000 words or more for Exhaustive reports. The tool supports file uploads and lets users compare outputs across models. Live web research depends on whether the selected model supports web tooling; without it, a report relies on that model’s training data. Listed uses include market research, competitive analysis, due diligence, journalism, academic reviews, policy analysis, and meeting preparation. The free plan includes 250 starting credits, access to AI models using credits, web search and file analysis, and one custom agent. Plus is $16.67 a month when billed annually, or $20 a month with monthly billing. The maker advises checking sources and details before relying on high-stakes claims.

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.