Collect workflow
Collect public sources and preserve URLs, dates and relevance.
AI agent roles · AI research agent
AI Research Agent for Controlled Business Research
Turn recurring market, competitor and operational research into a sourced workflow with structured reports and visible uncertainty.
Customer-owned AI keysPer-agent permissionsHuman approval gatesExecution history
Your modelApproved toolsHuman reviewAudit history
AI research agent
in RentAgents
in RentAgents
Where it fits
A focused workflow with a clear owner.
Research fails when the brief is vague, sources disappear or a confident summary hides weak evidence. This role follows a saved method, records links and separates evidence from interpretation. A specialist role is safer and more useful than one universal bot. Each role below has a defined purpose, a narrow evidence set, explicit escalation and a human owner.
RentAgents is not a promise that a model can operate a business without supervision. The customer selects the AI provider, defines permanent instructions and decides which web, browser, file, Python, messaging or desktop capabilities are justified. The safest deployment begins with preparation and read-only work. Permissions are expanded only after the team has tested normal cases, failures, malicious inputs and ambiguous requests.
Practical scope
What the workflow can support.
The exact result depends on the selected model, customer data, connected systems and permissions. These capabilities describe controlled starting points rather than guaranteed autonomous outcomes.
Compare workflow
Compare authorised files and identify agreements, differences and gaps.
Prepare workflow
Prepare evidence tables, research briefs and decision memos.
Use workflow
Use controlled Python for calculations, deduplication and validation.
Flag workflow
Flag conflicting claims and low-confidence conclusions.
Run workflow
Run approved scheduled monitoring on a defined topic.
Deployment method
A four-step controlled operating model.
A production-ready ai research agent should have a named owner, written acceptance tests and an escalation path. Tests should include outdated information, missing files, contradictory instructions, provider errors and requests that exceed the role. The team should review correction rates and task history rather than judging the workflow from one impressive demonstration.
Define the question, acceptable sources, date range and output.
Gather evidence and record why each source matters.
Analyse the material and expose gaps or contradictions.
Have a person verify the evidence before the result is used.
Control layer
Authority is explicit.
- Define the job in permanent instructions and prohibit decisions outside that role.
- Give the role only the files, channels and tools needed for the job.
- Require review before external messages, account changes or irreversible actions.
- Use execution history to improve the role after every exception.
- Customer agent tasks use customer-owned provider credentials, and the provider bills that customer account directly.
- Task, tool, channel, approval and authorised desktop activity can be reviewed in the operational history.
Expected value
What a successful deployment improves.
- More consistent ai research agent work because the role follows saved instructions and output standards.
- Less manual preparation while external decisions and commitments remain human-controlled.
- A clearer record of evidence, tool use, exceptions and approvals for improvement and investigation.
Important limitation: Public information can be outdated or false, and the model can misread context. High-impact conclusions require primary evidence and qualified review. AI outputs and actions can still be wrong, and a responsible person remains accountable for final use.
Questions
Frequently asked questions.
Can it cite sources?
Yes. The instructions can require URLs and evidence notes when web tools are enabled.
Can it analyse private files?
Yes, when the relevant files are placed in the authorised customer workspace.
Can I customise the role?
Yes. Start from a structured template or create a custom agent with permanent instructions, selected models, tools and limits.
Does the agent make final decisions?
It should prepare, organise and propose. Consequential decisions remain with an authorised person.
Related workflows
Build a small team of specialist agents.
Test this workflow with your own model account.
Start with one narrow task, keep external actions in approval mode and inspect the execution history before expanding access.
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