Clay vs Lantern: a direct comparison for enterprise revenue teams

Two different theories of what a data platform should do

Clay and Lantern both touch enrichment. That's where the overlap ends.

Clay is a flexible enrichment workflow builder. It lets you pull from 100+ data sources, build waterfall enrichment logic, and run research automations via its AI agent, Claygent. For growth teams and GTM engineers who want maximum flexibility and are willing to build the workflows themselves, Clay is genuinely powerful.

Lantern is a Revenue Data Platform built for enterprise. It aggregates 150+ enrichment providers, builds a custom Revenue Ontology specific to your business, deploys AI agents that run autonomously, and pushes everything back into Salesforce and your downstream tools automatically -- with forward-deployed engineers who own the deployment.

The comparison below is specific and direct.

Clay vs Lantern: head-to-head

Data sources and coverage

Clay connects to third-party enrichment providers only -- typically 100+ sources through its waterfall model. Coverage is strong for standard firmographic and contact data.

Lantern connects to 150+ third-party providers and also ingests first-party data: CRM history, product usage data, support interactions, and behavioral signals. The combination of third-party enrichment and first-party context in a single unified model is what makes the scoring decisions more defensible.

Implementation model

Clay is self-serve. There is no implementation support. You build the enrichment tables, you maintain the workflow logic, you fix things when they break. This is appropriate for a growth team with a dedicated GTM engineer. At enterprise scale -- with complex account hierarchies, territory structures, and multiple product lines -- the self-serve model is a constant maintenance burden.

Lantern includes forward-deployed engineers with every enterprise contract. They're in your Slack channel, not behind a support ticket queue. They configure your integrations, build your Revenue Ontology, deploy your agents, and optimize workflows on an ongoing basis. Most customers are in production within 3 weeks.

Workflow execution

Clay uses linear enrichment tables. Claygent can run research tasks, but the execution model is sequential: you define the steps, it follows them. There's no native branching logic, no autonomous multi-step execution, and no real-time signal response without manual workflow maintenance.

Lantern's agentic branching builder creates multi-step workflows that research, decide, branch, and execute autonomously. When a champion job change fires, the agent doesn't just log it -- it researches the new company, scores the account, updates the Salesforce record, notifies the rep in Slack, and triggers the appropriate sequence in Outreach. The entire chain runs without a human in the loop.

CRM sync

Clay enriches data in tables. Getting that data into Salesforce requires a separate export, a Zapier integration, or a reverse ETL tool you build and maintain yourself. In practice, this means enriched data often stays in Clay tables rather than making it into the CRM.

Lantern has bi-directional real-time sync with Salesforce and HubSpot. Enriched, scored data updates CRM records automatically. When a signal fires, the CRM field updates immediately -- no export, no import, no lag.

Data model

Clay's data model is generic. Every customer uses the same field structure and the same waterfall logic. The platform doesn't know what "enterprise" means for your business, how your territories are structured, or which signals matter in your specific market.

Lantern's Revenue Ontology is custom per customer. It encodes your account hierarchies, territory logic, ICP definitions, and signal-to-action mappings into the data layer. The agents' decisions are grounded in your business context, not a generic template.

Voice

Clay has no voice capability. Lantern includes voice agents for inbound and outbound qualification calls -- part of the same agentic workflow layer, not a separate integration.

Security and compliance

Clay has limited enterprise security certifications. Lantern is SOC 2 Type II, GDPR, and CCPA compliant, with single-tenant deployment available for enterprise customers.

The honest version of who each platform is right for

Clay is the right tool if you have a dedicated GTM engineer or technical co-founder, you're a growth-stage company with relatively simple data needs, you want maximum flexibility to build custom workflows, and self-serve is a feature rather than a limitation for you.

Lantern is the right tool if you're an enterprise RevOps team that needs the platform to work out of the box, you need enrichment data to live in your CRM -- not in separate tables, you want AI agents that act on signals autonomously rather than requiring manual workflow maintenance, and you need a team that owns the deployment alongside yours.

The number that frames the decision

One Lantern customer generated $7.6M in pipeline in their first 60 days -- Shubh Sinha, VP. That's not a self-serve result. It requires a platform configured for your specific business, deployed by engineers who know both the tool and your motion.

If you're evaluating whether Lantern is the right fit for your team, see a side-by-side walkthrough with your current stack.