System/Integrations/Integration
Clay
Intent & enrichment
Clay runs a waterfall across more than a hundred data providers, filling gaps until a company or contact record is complete. Revenue Labs reads what Clay returns and writes it into account and contact state, so an enriched field becomes something every rep can act on.
Website
From source record to operating state
01 | The tool on its own
Waterfalls query providers in order.
↓
02 | With AI bolted on
Research and enrichment stay in Clay.
↓
03 | A system that learns
Returned fields join account evidence.
The tool alone > AI bolted on > AI-native
What changes when Clay feeds a system that learns
Three jobs Clay already does, and what each becomes when its evidence joins live company, contact and deal state.
01 | The tool on its own
02 | With AI bolted on
03 | AI-native
Waterfall enrichment
Waterfalls query providers in order.
Clay searches data providers sequentially until it finds a usable result. An operator still chooses the order, monitors credits, and checks the returned field before it is used.
Research and enrichment stay in Clay.
Clay's agents and web research return findings inside Clay. They remain provider and prompt scoped, with no shared deal history to explain whether the result mattered.
Returned fields join account evidence.
Clay's returned field joins the matched company or contact with the rest of its evidence.
Tables and workflows
Tables turn rows into workflows.
Clay tables connect sources, transformations, and actions around each row. Operators still set the logic, review errors, and decide when an output is ready to use.
Workflow generation stays in Clay.
Clay can create research functions and enrichment workflows from instructions. The logic remains in Clay and does not learn from the later deal outcome.
Next run sees the whole state.
Returned fields are read alongside conversations, activity, and deal state instead of treating the table row as the whole context.
Research columns
Research columns add context to a row.
AI web research can read pages and documents and place findings beside a person or company. A researcher still validates the result and decides which context belongs in the motion.
Research explanations stay in Clay.
The research summary is useful within Clay, but it cannot show which source detail changed a deal or whether the recommendation worked.
Enrichment weight changes with results.
On the next account, enrichment uses the fields the system learned were associated with progress, loss, or silence.
Runs on it
Capabilities that act on connected evidence
BUILT FOR SECURITY, CONTROL AND SCALE
Connect data securely, capture every agent's activity, and enforce permissions with ease.
Learn about our security →CERTIFIED + COMPLIANT WITH:
ISO 27001:2022
GDPR
CCPA
Data Protection Act 2018
The GTM teams that learn fastest will win.
Connect your stack to a system that learns.