Skip to main content
Incomplete CRM data slows everything down — reps waste time looking up basics, lead routing breaks, and reporting becomes unreliable. An enrichment Agent fills in the gaps automatically so your data stays clean without manual effort.

​
When this pays off

Routing rules can't fire

Lead-routing logic depends on fields that are blank for half the records.

Unreliable reporting

Industry and company-size data is inconsistent, so segmentation reports are useless.

LinkedIn URL as research

Reps are pasting LinkedIn profile links into the CRM and calling it enrichment.

New ICP rollout

You’re redefining your ICP and need to re-evaluate every existing record against the new lens.

​
The shape of this use case

An enrichment Agent takes a partial CRM record and fills in missing fields.

Inputs

Existing CRM record (contact or account) with partial data.

Sources

Web search, LinkedIn, third-party data vendors, your own CRM history.

Output

Filled-in fields — firmographics, contact details, tech stack, social profiles — with source attribution.

Delivery

Written back to the CRM in the correct fields, with sourcing notes attached.

​
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 Elli, the Enrichment Agent. More in the Marketplace.

Build your own

Start from scratch in the builder, or by describing it in Claude Code or Cursor with Programmatic GTM.
Either way, these are prompts your reps can use on day one:
  • “Enrich Acme Corp — fill in industry, employee count, and any recent news.”
  • “Find the head of RevOps at Initech and add them as a contact in HubSpot.”
  • “What tech stack is Globex running? Web search and check LinkedIn.”

​
Where to take it

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

Give it a playbook

Shape it with a prompt, a connected CRM for read/write, and rules in Knowledge.

Automate it on signals

Wrap it in a workflow that fires on a trigger.

Let it improve

Tune it through evals so it maintains the fields your team actually uses.

​
Common pitfalls

Credit-burn at scale. Gate enrichment on lifecycle stage and a freshness window — don’t re-enrich records that were updated last week.
A rep’s hand-typed value usually beats whatever the web returns. Preserve human overrides, or write to a parallel “enriched_*” field that reports can choose to use.
Reps can’t trust a value if they can’t see where it came from. Have the Agent attach a source URL and timestamp to every enriched field.
Pulling 2019 data into a 2026 record looks like enrichment but isn’t. Filter sources by recency where it matters — leadership, headcount, funding.