Inbound lead research and outreach
Research each inbound lead and prepare a cited, personalized first touch for approval.
What this workflow does
Research each inbound lead and prepare a cited, personalized first touch for approval. It produces a source-linked draft, validates it against policy, and keeps publication or system updates behind an explicit approval.
What you gain
Research brief
What the AI agent changes
How this worked before
Templates could merge known fields, but they could not understand source documents or adapt the draft to exceptions.
What the AI agent changes
The agent reads source material, drafts the right version for the case, cites evidence, and leaves the final send or write to a person.
Agent trigger
A new inbound lead is created with a business email.
Inputs
- Lead and campaign fields
- Approved public research sources
Agent flow
- 1
Verify person and company identity.
- 2
Research role, priorities, and relevant signals.
- 3
Draft a source-backed message and next step.
- 4
Send only the approved draft and log it.
Human decisions
After step 3
SDR approves facts, tone, and send timing.
Outcome
- Research brief
- Approved outreach logged in CRM
Guardrails
- Use only approved public sources.
- Cap send volume per owner and domain.
Risks and mitigations
Hallucinated facts can damage trust.
Attach a URL to every external claim and block uncited personalization.
Sources and evidence
Sources establish feasibility or impact. Not every metric comes from an identical implementation.
OpenAI
Clay uses OpenAI to scale go-to-market work
Clay combines research, enrichment, and personalized outreach in repeatable go-to-market workflows.
Riley Brown on X
Multi-step agent workflow example
A practitioner demonstration shows a multi-step agent moving from research to actions in connected tools.