ClayClay
Enrichment waterfalls and agentic research
Clay sits upstream of the CRM, chaining dozens of data providers into a waterfall and layering AI research on top to build lists that would otherwise take a research team. It is the sharpest tool in modern outbound and the easiest to overspend on.
[ 01 ] The verdict
Genuinely capable of replacing a research function, and the waterfall approach materially beats any single data vendor. It rewards operators who understand unit economics and punishes those who do not.
Best for
Revenue operations teams building highly targeted lists with research-heavy qualification criteria.
Watch out
Credit burn is the number one complaint. Build with a small sample, measure cost per enriched record, then scale.
Strengths
- Waterfall enrichment materially improves match rates
- AI research agents handle criteria no data vendor sells
- Deep integration with sending and CRM tools
- Strong community of shared templates
Trade-offs
- Steep learning curve for the full capability
- Credit consumption is easy to underestimate
- Outbound at this scale carries real deliverability risk
[ 02 ] What it actually does
What Clay actually ships.
Enrichment waterfall
Falls through multiple data providers in priority order, paying only for the first match.
Claygent
AI research agent that visits sources and answers qualification questions per record.
Table workspace
Spreadsheet-shaped interface where every column can be a provider, formula or agent.
Signal triggers
Build lists from hiring, funding, technology and news events automatically.
[ 04 ] Clay alternatives
