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Reps spend hours digging through LinkedIn, company websites, and news to prep for a single call. Relevance can produce the same brief in seconds — at whatever level of automation you’re ready for.

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When this pays off

High call volume

Reps run more than five discovery calls a week and prep is eating their selling time.

Uneven prep

Some calls get deeply prepped, others get a quick scan — output quality is inconsistent.

Inbound triage

Inbound leads need quick context before a rep is assigned.

Baseline context

Every meeting starts with the same baseline brief, not whatever the rep happens to find.

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The shape of this use case

A prospect research workflow takes a company name or contact and returns a structured brief.

Inputs

Company domain, contact email, or CRM record.

Sources

Web search, LinkedIn, news, your CRM, and any internal knowledge — ICP, personas, battle cards.

Output

A brief covering company overview, recent news, key contacts, likely pain points, and conversation hooks.

Delivery

Returned inline, posted to Slack, written back to the CRM, or attached to a calendar event.

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Where to start

Two ways in, depending on whether you want something running today or built to your exact spec.

Clone a pre-built Agent

Open the Sales Researcher — or Lia for LinkedIn-first. More in the Marketplace.

Build your own

Start from scratch in the builder, or by describing it in Claude Code or Cursor with MCP & Plugins.
Either way, these are prompts your reps can use on day one:
  • “Research Acme Corp ahead of my 2pm call. Pull recent news, the buyer’s LinkedIn, and any open deals in HubSpot.”
  • “Summarize the last three meetings with Globex and what’s still open.”
  • “Who at Initech should I be talking to if we’re selling into RevOps?”

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Where to take it

Once it’s running, deepen it in three moves:

Give it a playbook

Shape it with a prompt, Knowledge, and Bulk Schedule.

Automate it on signals

Wrap it in a workflow that fires on a trigger.

Let it improve

Feed won-deal signals back into the Agent’s evals so it tracks what closes.

Walkthrough — build an AI sales research agent that preps call-ready briefs from a name.

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Common pitfalls

Gate the trigger on lifecycle stage so you don’t burn credits re-researching closed-won customers.
Without an ICP or persona in knowledge, the output reads like a Wikipedia summary. Add the lens.
Set a freshness window — e.g. re-research only if the last brief is more than 30 days old — instead of regenerating on every interaction.
Web search returns whatever ranks, not what’s true. Cite sources in the brief so reps can spot-check.