Clay Sculptor Review October 2025

Clay announced Sculptor in 2025 as their “biggest release yet”. It is an AI copilot with natural language input that can build workflows and analyze datasets in Clay’s GTM platform. Fundamentally, it just lets you build in Clay faster.

This represents one of the next steps in Clay’s vision for their platform and broader GTM. Clay’s timing is significant, having just raised a $100 million Series C at a $3.1 billion valuation. Its annual recurring revenue is tripling year over year, on track towards $100 million in 2025.

Research by Gartner states 70% of businesses believe AI in GTM is critical to success in the coming years. A major 60% of teams are planning to increase investment in AI-native marketing and sales tools in 2025.

Clay is known for its data quality and enrichment value, but the Sculptor launch helps it to compete on user experience and time to value as well.

This review was informed by detailed initial research, interviews, analysis and finally individual testing.

What is Clay Sculptor?

Core functionality

Natural language workflow building

Clay Sculptor lets users request complex operations in natural language, like “find CMOs at education technology companies in San Francisco” or “analyze this list of deals and produce reasoning for why we lost each deal”.

Business context awareness

Sculptor has the impressive advantage of Clay’s own GTM knowledge and experience. They say that Sculptor “combines years of go-to-market experience with your business context to tailor every recommendation to your unique GTM motion.”

High quality data is how you produce uniquely valuable results in the world of AI, and Sculptor buys into that philosophy.

Real-time data analysis

Identify patterns, prioritize specific targets and fetch instant insights. Sculptor is able to do genuinely useful data analysis fast.

Iterative debugging

This feature has been celebrated by many users. Clay Sculptor explains errors in plain language allowing even non-technical users to fix bugs fast and easily.

As the world moves towards AI-enabled workflows, catering for both the non-technical and technical will form a core differentiator and advantage for platforms.

Key capabilities

Table building

Sculptor guides table setup by ingesting ICP (Ideal Customer Profile) information from your own business context. This allows you to provide relevant recommendations and take proactive steps when building out your workflows. This is an enjoyable step towards the proactive AI workflows much of the market is after.

Accelerated setup via natural language

The future of building is arguably in natural language. Clay states that Sculptor allows users to “talk like a human” to configure tables in “a fraction of the time”. In first party testing, the natural language building felt natural and aligned with my expectations, which is not a given. Some natural language tools can feel extremely frustrating to build with, as the tool misunderstands your intent and builds something else (looking at you Zapier copilot).

Market context : The AI copilot trend of 2025

The broader trend of AI copilots

Clay is definitely not the first AI copilot to market. Generative AI is now the most popular type of AI solution deployed according to a Gartner survey. Gartner also quote that 34% of organizations use Generative AI embedded in existing applications as their primary method i.e. copilots, instead of standalone tools or custom internal applications.

Forrester research predicts 80% of businesses will adopt AI-powered marketing and sales tools by 2025, with Microsoft, Salesforce and many big enterprise platforms all launching copilot platforms, establishing natural language input as a primary interface going forward from 2025.

Why natural language matters for GTM tools

Natural language matters in GTM because it is all about time to value, and accommodation of a wide range of technicality. GTM teams typically contain both technical and non-technical users, and both of these types of users benefit from natural language input.

It reduces time from idea to execution, which is a critical component of successful GTM teams. Clay itself states this “GTM teams aren’t bottlenecked by ideas, they’re bottlenecked by execution” and position Sculptor as a solution to this.

The “GTM Engineering” movement clay is pioneering

Clay coined the term “GTM engineering” first in 2023, and since an entire job category has emerged, using Clay, but also others.

Over 280 GTM Engineer positions now exist at top-tier companies like Cursor, Webflow, Notion and Lovable and 7 independent bootcamps have graduated over 2,500 students in GTM engineering. Sculptor represents yet another tool in the GTM engineering kit, and will be well received by people in the discipline who above all want to execute faster.

Competitive analysis: how Sculptor differentiates Clay

Clay’s core position

Not a traditional data provider

Clay aggregates data from 150+ providers using “waterfall enrichment” rather than owning a traditional database themselves. They position themselves as a “GTM development environment”( from the Clay blog) comparable to how IDEs transformed software development.

Clay tries to be AI-native. Much discussion has referred to legacy software “bolting-in” AI features, and Clay aims to be a tool built with AI at its core.

Direct competitors and their approaches

Apollo.io

Apollo own a database themselves of 275 million plus contacts with built in sales engagement. They use credit-based pricing starting at $49 per user per month. It currently has no equivalent natural language copilot feature (when we checked) and positions themselves as “one platform to close them all”, competing on consolidation and price.

ZoomInfo

ZoomInfo is the enterprise incumbent. Like Apollo, they own their own database with 420 million contacts and proprietary data collection technology. They do have a copilot feature, providing account prioritization recommendations and analysis.

Starting at $15,000 and more a year, it is significantly more expensive than Clay. Interviews and first party testing indicate it has much better coverage in North America than Europe.

Cognism

Cognism is a compliance focused European centric competitor. They have a strong GDPR and CCPA compliance focus, with global coverage, but notably leading EMEA data. It has a Sales AI Companion, but it is not a full workflow builder like Sculptor. There is no waterfall enrichment, as they use a single source of data : Diamond Data phone-verified mobile numbers with 87% connect rates.

They position themselves as leading option in compliance and quality compared to Clay and others.

Clay’s unique value propositions

Flexibility versus control

Clay offers maximum customization through its builder, while competitors provide simpler out of the box experiences but with less flexibility. Sculptor aims to bridge this gap, offering flexibility without the complexity. One comparison notes that “Clay is more customizable; Apollo is more out of the box”.

Multi source data strategy

Clay’s waterfall approach allows coverage across 250+ providers versus single source databases of competitors. This is an obvious advantage.

Clay achieves higher coverage by trying multiple sources sequentially, but introduces some compliance complexity since not all providers are equally compliant. Cost can escalate quickly with a credit based system.

Operations vs sales focuses

Clay is more heavily targeted towards RevOps and GTM engineers than it is directly to Sales. This is in contrast to ZoomInfo and Apollo, which are more heavily targeted to Sales. Sculptor likely enables Clay to broaden its audience and appeal to less technical members across the GTM function like Sales.

ZoomInfo notes “Clay appeals to smaller operations teams who love building complex data workflows”.

Early reception and user feedback

Positive user testimonials

Time savings: “I thought Sculptor would mostly help people less familiar with Clay, but as the main power user at my org, it helped me get in 15 minutes what usually takes a couple of hours. Pretty wild.” https://www.clay.com/sculptor
Model testing efficiency: “Sculptor saved me a ton of time by letting me test multiple models on company data, compare outputs, and skip all the manual exporting and duplication I’d normally have to do.” https://www.clay.com/sculptor
Training reduction: “Instead of training teammates for hours, I can point them to Sculptor and it builds the same searches I would, saving me huge amounts of time.” https://www.clay.com/sculptor
Customization capabilities: “Sculptor let me customize prompts and surface exactly the people I needed, saving tons of time I’d usually spend tweaking on my own.” https://www.clay.com/sculptor

What Sculptor addresses

The “steep learning curve” criticism of Clay often quoted in comparison to other tools
Natural language interface reduces need for technical skills and increases time to value
Context-aware recommendations remove guesswork from setup, and allow for proactive AI workflows.

Conclusion

Sculptor is an impressive technical achievement, and moves Clay to the forefront of the natural language wave. Launching a sophisticated AI copilot alongside multiple other recent features shows exceptional execution from the team, and early user testimonials and our own research indicate there are real time savings and benefits.

But, impressive now doesn’t mean impressive in the long term. Some core questions remain:

Will Sculptor continue to develop at the frontier of natural language copilots?
Do ease-of-use capabilities cannibalize Clay’s core user base of power users and GTM engineers who aren’t afraid of complexity?

The race is just beginning, and copilots like Sculptor are just the starting line. The next evolution is a shift towards more and more proactive workflows where agents execute strategies end to end, and Clay’s roadmap suggests they too are heading towards this. Therefore, how Sculptor forms part of this will be interesting to watch.

Sculptor is definitely worth testing, especially if Clay’s complexity has been a barrier for your team, and Clay has earned the right to be taken seriously as a platform for broader GTM, not just in the AI field. Very excited to see what they release next.