PulseLakeResearch capabilities for AI assistants and interviews
Compare connected research workflows, evidence access and AI-assisted execution against the job you need done.
Relevant capabilities
- AI-led interviews with real participants
- Evidence-linked analysis and research context
- Research design, analysis and delivery workflows
How should you compare the options?
- Specify the research jobs an assistant needs to perform; tool connectivity alone is not a research methodology.
- Require evidence provenance and human review for decisions that depend on participant findings.
- Confirm the actual connector, permissions, supported actions and export formats in a small test.
What should you bring?
- Assistant or agent environment and intended tasks
- Study types, data boundaries and approval requirements
- Required evidence and export formats
What does a practical first workflow look like?
- Map the desired assistant workflow to supported research capabilities.
- Confirm access, permissions and required human approvals.
- Run a bounded pilot with a representative study.
- Review evidence, failure handling and outputs before increasing autonomy.
What should you check before expanding?
- Confirm that the tool only accesses authorized studies.
- Inspect citations and links behind material findings.
- Verify what happens when a tool fails or a required input is missing.
How should you evaluate the cost?
Compare the full workflow cost, including participant access, compute usage and researcher review, rather than model usage alone.
What needs checking before switching?
Verify the specific connector, tool permissions, supported study types and export formats for your environment.