Every tool below is a legitimate way to find and enrich B2B contacts, and each is strong at a different part of the job: breadth, price, scientist-level depth, phone accuracy, or raw configurability. None of them, on their own, know whether a company is a good life science fit, or what function and seniority actually make up a CRO, CDMO, or life science tools buying committee. That gap is what a life science-specific lens is for.
What each sales intelligence tool is actually good at
Arcova has a deeper, dedicated comparison for each of these if you want the full breakdown: ZoomInfo, Apollo, SciLeads, and Clay.
Quote-only, typically five figures a year for a small team and scaling well past that
One of the largest and most maintained B2B contact and company databases on the market, with org charts, direct-dial phone numbers, and intent data that works the same way across every industry.
Best for: Teams that sell horizontally across many industries, or that have the budget and process maturity to run a large enterprise data contract well.
Free tier, then per-seat credit-based plans typically running from the high double digits to around $100+ per user per month
A large, searchable database across every industry with a built-in sequencer and dialer, giving small teams contact discovery and sending in one affordable, self-serve platform.
Best for: Smaller teams or budget-conscious teams that want an all-in-one prospecting-plus-sending workflow without a second system to manage.
Quote-only, via demo
The deepest database of research scientists in life science, more than 18 million individuals and 430,000+ pharma and applied science organizations, sourced from publications, grants, and tradeshow activity.
Best for: Teams whose actual buyer is the bench scientist or principal investigator, found by tracing a publication, grant, or conference poster back to a name.
Quote-only; real-world deals commonly range from the low thousands to $25,000+ per year depending on tier and team size
Phone-verified mobile numbers with a high accuracy rate, unrestricted contact exports rather than a credit-metered model, and strong European data coverage via a Bombora intent-data partnership on its higher tier.
Best for: Enterprise outbound teams that lean on calling as a channel, or teams with meaningful EMEA exposure alongside their US book.
Free tier, then usage-based plans scaling from roughly the low hundreds to several hundred dollars a month, with custom enterprise pricing above that
A spreadsheet-like canvas that waterfalls over a hundred data providers together and runs AI research agents on each row, so it can be pointed at almost any enrichment problem, life science included.
Best for: Teams with technical RevOps capacity that want a fully custom, provider-agnostic enrichment workflow they design and maintain themselves.
The stitching burden vs. one life science-native motion
A realistic life science data stack often runs two or three of these tools at once: a broad database like ZoomInfo or Apollo for discovery, maybe SciLeads for scientist-level targeting, and Clay or a similar workflow tool to stitch the outputs together and try to approximate a life science fit score by hand, therapeutic area matching, modality overlap, and stage logic written and maintained as custom rules. Every provider added to that stack is another export to keep in sync, another field mapping to maintain, and another place fit criteria have to be re-implemented from scratch.
Arcova does not try to out-cover any of these databases. It unifies a narrower, specific motion end to end: score the accounts and contacts you bring in, from any of the tools above or your CRM, against a life science ICP built on therapeutic area, modality, and development stage, layer in the readiness signals that matter in biotech and pharma, and prioritize the resulting list. That model comes configured already; nothing needs to be designed in a workflow canvas first.
Choosing between them
If you sell horizontally and life science is one segment among several, ZoomInfo's breadth is hard to match. If budget and simplicity matter more than coverage depth, Apollo is the practical starting point. If your buyer is the bench scientist rather than a commercial decision-maker, SciLeads is a different, more specialized tool worth adding rather than replacing anything on this list. Cognism is worth a look specifically for phone-verified mobile coverage or EMEA exposure. Clay is the right call only if you have the engineering time to build and maintain a custom workflow, since its flexibility is real work, not a configuration toggle.
None of these choices resolve the harder question underneath them, covered in how to prioritize accounts: once you have the data, which accounts are actually worth working, and when.
For the signal side of this same problem, see the best buying-signal and intent tools for life science.