Deep Research
The Deep Research block retrieves information from the web based on a research request you provide.
Research topics by sourcing information from the web
The Deep Research block retrieves information from the web based on a research request you provide. It uses Google Search and web scraping to gather source material on a given topic, then returns the results in a structured format. This makes it useful when a workflow needs to pull in current or external information rather than relying solely on a model's training data.
The block takes two inputs: a research request string, which is the prompt or question driving the research, and an output type that controls the format of the returned results. You can choose between markdown, XML, or JSON depending on how downstream blocks in your workflow will consume the data.
The block returns a single output variable called research, which contains the gathered results in whichever format was specified. This output is well-suited for passing into a model call for summarization, analysis, or report generation. Workflows that involve competitive analysis, content creation, fact-checking, or any task requiring up-to-date external information are common fits for this block.
What you can build
Real-world workflows powered by the Deep Research block.
Competitive Market Analysis
Automatically gather current information about competitors or market trends and feed the results into a model block to generate a structured analysis report.
AI-Generated Research Reports
Use the block to source background information on a topic, then pass the output to a language model to produce a formatted research report.
News and Topic Monitoring
Run recurring research requests on specific topics to surface recent web content, enabling workflows that track developments over time.
Product or Service Lookup
Retrieve publicly available information about a product, service, or company to support sales enablement or due diligence workflows.
Content Brief Generation
Research a subject area and pass the structured output to a model block that drafts content briefs or outlines for writers.
Fact-Checking and Verification
Supply a claim or statement as the research request and use the returned web-sourced results to support or challenge the input within a validation workflow.
Ready to add Deep Research to your workflow?
Get Started FreeCommon questions about Deep Research
What inputs does the Deep Research block require?
The block requires two inputs: a research request string, which is the prompt or question you want researched, and an output type that specifies the format of the results. The output type accepts one of three values: 'markdown', 'xml', or 'json'.
What does the block return?
The block returns a single output variable named research, which contains the gathered results formatted according to the output type you selected. This can be markdown text, XML-tagged content, or a JSON structure.
What kinds of workflows is this block commonly used in?
This block fits workflows that need external or current information, such as research report generation, competitive analysis, content creation, and fact-checking. The output is designed to be passed into a model call for further processing.
Which output format should I choose?
The choice depends on how downstream blocks will use the data. JSON is useful if a subsequent block needs to parse structured fields. XML-tagged output is noted as ready for use in model calls. Markdown may be preferable for display or text-based processing.
Does this block require any API keys or external credentials to configure?
No API keys are required. The Deep Research block is a packaged workflow capability available directly within MindStudio without additional credential setup.
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Add Deep Research to your workflow
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