Clay
Marketing · Usage-based
Overview
A data tool for go-to-market teams. You start from a list of companies or people, then Clay fills in details about them by checking many data providers and by sending an AI agent to read the web. The result is an enriched table you can push into a CRM or an outreach tool. Clay was founded in 2017 in New York by Kareem Amin and Nicolae Rusan. It sits between a spreadsheet and an automation platform, and is used mainly by sales, marketing, and revenue operations people who build targeted prospect lists and keep CRM records current.
What people use it for
Sales and revenue operations teams use Clay to build targeted prospect lists: start with a set of companies that fit, then pull in headcount, funding, tech stack, contact names, verified emails, and phone numbers. They use it to keep a CRM clean by re-checking and filling missing fields on a schedule. Marketers use it to score and route inbound leads by enriching form submissions in real time. Teams use Claygent, the AI research agent, to answer questions that structured data cannot, for example whether a company runs a certain type of program or mentions a specific initiative on its site. Others use Clay to find lookalike accounts, to dedupe and normalize messy lists, and to prepare personalized details for outreach sequences before sending them to an email tool.
Key capabilities
Clay connects more than 200 data providers in one place, so a single lookup can try several sources in sequence, called a waterfall, and stop when one returns a good answer. This applies to emails, phone numbers, and firmographic fields, and raises match rates compared with any one provider. Claygent is an AI agent that takes a written prompt, searches public web pages, and returns a specific data point per row; the company says it has passed a billion runs. Tables support formulas, filters, and conditional steps, like a spreadsheet with automation built in. Clay integrates with CRMs such as Salesforce and HubSpot, with outreach tools, and with ad platforms including LinkedIn, Meta, and Google for audience syncing. It has a Chrome extension and an API. Pricing is credit-based: each enrichment or agent run consumes credits, and plans differ by monthly credit allowance and feature access. Running out mid-month means buying top-up credits at a surcharge on top of the plan rate.
Limitations
Clay is hard to learn. Reviews describe four to six weeks of real onboarding, and it is not something you hand to an SDR team and expect results the next week. The credit model is the other issue: costs are hard to predict, users report burning hundreds of dollars just learning the interface, and top-ups after you run out are billed at a 50 percent surcharge over the plan rate. For a small team that only needs a simple contact database, it is more tool than the job requires. Data quality still depends on the underlying providers, so results vary by region and by how obscure the target is.
Insight
Clay is powerful for building precise, enriched lists that would take days by hand, and the waterfall approach genuinely does beat relying on one data vendor. But two things trip people up. First, the learning curve is real, and a team that does not commit time to it ends up using a fraction of what it pays for. Second, credit-based pricing punishes experimentation: the try things phase can quietly cost hundreds, and once you run out mid-month the top-up surcharge stings. Treat the first month as training, not production, and set a credit budget before anyone starts building. It rewards a dedicated operator who owns it and learns it well, and frustrates everyone who expects to dip in occasionally. For the right person it replaces a stack of separate data subscriptions.
Pricing
Usage-based
Website
Last checked 2026-08-30