What Is Claygent?

Where Claygent fits in a prospecting workflow

A data lookup and a research question ask for different things. One might request a known company attribute. The other might ask whether a business offers a particular service and require evidence from its website before classifying it.

Clay's Claygent Builder documentation describes building, testing and deploying agents for tasks such as research, scoring and persona classification. Its AI overview explains the research role alongside other AI features. Product names and capabilities can change, so use those current references when designing a run.

Before starting, decide where the answer will go. A research result intended to exclude unsuitable accounts needs a different review policy from a note used to help a salesperson prepare for a call. The same output should not silently become both a qualification verdict and a factual claim in an email.

A bounded account-research example

Imagine the ICP requires companies that provide commercial cleaning. This is a conceptual example, not a claim about a client campaign or a measured success rate.

Give the research step the company domain and a narrow question: does the company's own website show that it provides cleaning for commercial premises? Ask for a decision, the supporting URL and a short explanation of the evidence. Allow "unknown" when the available information does not settle the question.

Now review contrasting examples: a clear commercial provider, a residential-only business and a site that does not state its market. Check whether the evidence actually supports each decision. A fluent answer that points to an irrelevant page is a failed research result, even when the wording sounds convincing.

Keep missing evidence separate from a negative answer

"Not found" and "does not offer it" are different conclusions. If the website is unavailable, vague or missing the relevant page, preserve that uncertainty. Otherwise a temporary research gap can become an incorrect exclusion or a personalization claim that the prospect immediately recognizes as wrong.

Define what a later step may use. For example, only evidence-backed classifications could pass a qualification gate, while uncertain records go to review. That is an operating policy to choose and test, not an automatic guarantee from the agent.

What to check before scaling

Test a small, deliberately varied set of records. Compare the returned evidence with the actual pages and record the failure types. Adjust the question or acceptance rule before increasing the batch.

Also inspect the current cost model and run conditions. Clay distinguishes Actions and Data Credits, so an estimated workflow budget should identify its components rather than assume a fixed price for every research question. No paid run is needed to understand the terminology.

For a fuller workflow, read the Clay AI enrichment guide. For a starting structure, see the account-brief prompt, then adapt its inputs and acceptance criteria to the decision you actually need.