Clay is one of the most flexible GTM tools available: a spreadsheet-like canvas where you wire together over a hundred data providers into a waterfall, run AI research agents on each row, and push the result anywhere. That flexibility is real power, and it is also work: every life science-specific rule, therapeutic area matching, modality overlap, trial-stage logic, has to be designed and maintained by hand. Arcova ships that model already built.
What Clay actually does
Clay offers a free plan with a modest allowance of data credits and actions, then paid plans that scale up from roughly the low hundreds of dollars a month for entry-level phone enrichment and signal tracking to several hundred a month for the tier that adds CRM sync, HTTP API access, and web intent data, with custom enterprise pricing above that. The core mechanic is a dual-credit system: data credits pay for the actual data pulled from Clay's 150-plus provider network, and actions pay for using the platform, enrichment steps, AI calls, and webhook pushes.
Clay's real strength is that it is not built for any one industry or use case. It can enrich a list for life science just as easily as it can for e-commerce or fintech, because the person building the workflow decides what data to pull and what logic to apply. That also means life science fit and readiness are not built in anywhere. They are something a team has to design themselves, row by row, provider by provider.
What Arcova adds on top
Arcova starts from the opposite direction: one industry, modeled in depth, with nothing to configure. Fit is scored on therapeutic area, modality, development stage, and similarity to your best customers, see building an ICP as a CRO or CDMO for how that model works, and readiness is built from the signals that actually matter in biotech and pharma, already interpreted for timing and reliability, not left as raw data points for someone to make sense of.
| Clay | Arcova | |
|---|---|---|
| What it is | General-purpose enrichment and workflow canvas | Life science fit and readiness layer |
| Setup | You design the workflow and logic | Model comes configured for life science |
| Industry scope | Any industry, provider-agnostic | Life science only, purpose-built |
| Life science fit and readiness | Possible to build, not included | Built in, no configuration required |
| Pricing | Free tier, then usage-based plans | Free to start |
When Clay is the better fit
If your team needs a general-purpose data and workflow layer across many use cases, not just life science account scoring, and you have technical RevOps capacity to build and maintain custom logic, Clay's flexibility is a genuine advantage a purpose-built tool cannot match. The same is true if your GTM pipeline needs to reach beyond scoring accounts, custom research agents, arbitrary API integrations, or workflows unrelated to fit and readiness, since that is exactly the kind of broad automation Clay is designed for.
Related comparisons
See how Arcova compares to ZoomInfo, Apollo, and SciLeads as well.