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| Dimension | Clay | 11x |
|---|---|---|
| Pricing tier | $$$ | Enterprise |
| Entry price | $149/mo | ~$5,000/mo (estimated; pricing not publicly listed) |
| Funding stage | Series C | Series A |
| Total raised | ~$165M | $20M |
| Target segment | Seed → Series B AI-native GTM teams; RevOps engineers | Mid-market and enterprise sales organizations seeking to replace or augment SDR headcount with autonomous AI agents |
| Dimension | Winner | Why |
|---|---|---|
| Pricing transparency | A EDGE | Claygent is included in Clay's credit-based pricing model — credits consumed per agent browse action, with published rates starting at $149/month for the Explorer plan. 11x's pricing is entirely sales-quoted with no published list price; community benchmarks put Alice contracts at $30,000–$60,000/year for a single AI SDR seat, with implementation fees layered on top. |
| ICP fit for SMB | A EDGE | Claygent is accessible to any Clay user from the $149/month plan — a GTM engineer at a 10-person startup can deploy Claygent research workflows without a sales engagement, contract negotiation, or implementation support. 11x's minimum contract size and sales-first motion effectively exclude companies under $5M ARR from a realistic evaluation. |
| ICP fit for enterprise | B EDGE | 11x's value proposition resonates most strongly with enterprise sales operations teams that are explicitly building a case for SDR headcount reduction — a narrative that requires executive sponsor buy-in and a multi-quarter ROI horizon. Enterprise teams with existing Clay infrastructure can extend Claygent without incremental vendor procurement, but 11x's autonomous-SDR story is more compelling at the organizational change management level. |
| Data quality / product depth | A EDGE | Claygent's browsing agent produces structured, reviewable research outputs — company news, hiring signals, technographic data, and custom extraction prompts — that a human operator validates before they flow into personalization and sending. 11x's research quality is opaque by design: Alice makes sourcing and enrichment decisions autonomously, and the quality is only visible in aggregate reply rate metrics rather than per-record inspection. |
| Integration breadth | A EDGE | Claygent inherits Clay's full integration surface — 100+ enrichment providers, native HubSpot and Salesforce sync, and Smartlead/Instantly sending integrations. The Clay ecosystem is the richest composable GTM stack available as of 2026. 11x integrates with Salesforce and HubSpot for CRM activity logging, but the integration surface is narrower because Alice is designed to own the workflow rather than feed into a broader stack. |
| AI-native features | Tie EDGE | Both are AI-native by design — Claygent uses LLM-powered web browsing and extraction; 11x runs an autonomous LLM agent across the full SDR workflow. The architectural difference is not AI capability but agency scope: Claygent is a narrow AI tool optimized for one task (research); 11x is a broad AI agent optimized for an entire job function. Neither is superior on AI capability alone. |
| Time to value | A EDGE | A Claygent research workflow on an existing Clay table can be configured and running in under 2 hours for a user already familiar with Clay's interface. 11x's implementation — ICP configuration, CRM integration, persona calibration, and sequence template approval — typically runs 2–4 weeks with dedicated onboarding support before Alice is sending at production volume. |
| Total cost of ownership | A EDGE | Claygent credits at Clay's Growth plan ($499/month) for a team running 1,000 agent-enriched prospects per month is a well-understood cost structure. 11x's $30,000–$60,000/year contract plus the internal oversight cost of monitoring an autonomous agent — reviewing reply handling, flagging off-brand sends, and managing escalations — often approaches or exceeds the loaded cost of a junior human SDR, eliminating the primary ROI justification. |
| Failure mode severity | A EDGE | Claygent's failure mode is a bad research output that a human catches at the review stage — the blast radius is one row in a Clay table. 11x's failure mode is autonomous sends to real prospects with misconfigured persona, wrong ICP targeting, or low-quality personalization — the blast radius is your entire domain reputation and the relationships of every prospect Alice contacted before someone noticed. The 1.0 cohort of fully autonomous AI SDR customers has produced enough public horror stories to make this failure mode a primary evaluation criterion in 2026. |
Choose Clay if…
– Your GTM stack is already built on Clay and you want to add agentic web research to your enrichment waterfall without a new vendor, new contract, or new interface to manage.
– You operate a human-in-the-loop outbound motion where a GTM engineer or RevOps operator reviews enrichment outputs before they flow into personalization and sending — Claygent’s modular architecture is purpose-built for this workflow.
– Your ICP requires custom research signals — recent funding, specific job posting language, competitor mentions, or technographic triggers — that standard data providers do not surface but a browsing agent can extract reliably.
– You have a tight budget and need agent capability without a $30,000+ annual contract — Claygent’s credit-based model scales with your actual usage.
Choose 11x if…
– Your organization has made an explicit board-level decision to reduce SDR headcount and needs a product that can demonstrate autonomous pipeline generation without daily human intervention — 11x’s full-stack AI SDR narrative is the only credible option for this use case.
– You have run a 90-day Claygent-enabled outbound motion and the bottleneck is human review throughput, not research quality — you need a platform that removes the human from the loop entirely, not one that makes the human more efficient.
– Your VP of Sales has a specific deliverable tied to AI-driven pipeline as a percentage of total pipeline and needs a vendor with an account executive, implementation team, and SLA to hold accountable — Clay’s self-serve model does not provide the vendor accountability layer that internal stakeholders require.
– You have validated 11x’s Alice quality on a pilot with your specific ICP and the reply rates are within 20% of your best human SDR — if the data supports it, the autonomy argument holds.