Most sales software waits for a human to decide what should happen next. Clay is raising $115 million to see whether the software itself can become better at making that decision.
The New York-based company has closed a Series D at a $7.1 billion valuation, led by Wellington Management, with backing from Sequoia, StepStone, a16z Perennial, Meritech, DST, CapitalG, BoxGroup, Boldstart, Bloomberg Beta and Evolution. Clay says revenue grew 4x in 2025 and its customer base now exceeds 17,000 companies, including Anthropic, Google, OpenAI, Stripe, Siemens and UPS.
The interesting part is not simply how quickly Clay’s valuation has risen. It is what investors are now valuing.
Clay’s valuation rose roughly 14× in just over two years
Clay was valued at $500 million when it announced its Series B in June 2024. A $40 million Series B expansion took that figure to $1.25 billion in January 2025, followed by a $100 million Series C at $3.1 billion that August.
In January 2026, employees were allowed to sell up to $55 million of shares in a tender offer pricing Clay at $5 billion. That was a secondary liquidity transaction rather than another primary funding round, an important distinction when tracking the company’s financing history.
The new $7.1 billion Series D therefore places Clay at roughly 14 times its June 2024 valuation.
That acceleration has followed a similarly unusual revenue curve. Clay crossed $100 million in ARR in December 2025, saying it had moved from $1 million to $100 million ARR in two years. Earlier this year, the company also reported enterprise net revenue retention above 200%, though these remain company-reported metrics rather than independently audited figures.
The Series D funds a feedback loop, not just more automation
Clay began in Brooklyn in 2017 as a programmable spreadsheet designed to let people connect data and automate work without writing code. Salespeople and growth teams eventually became its strongest users, pulling the company toward go-to-market infrastructure.
The product now stretches across data, AI agents, orchestration and execution. Clay combines CRM and product information with campaign engagement, calls and emails, then layers in outside signals such as funding events, hiring activity and job changes. Its platform also provides access to data from more than 200 providers alongside Claygent, Account Agents, Workflows, Ads and Sequencer.
The next ambition is different.
A team can describe a commercial goal in plain language and have Clay assemble an inspectable workflow around it. The system can find accounts, research prospects and prepare outreach. Clay says it then wants the platform to remember what prospects reveal, recognize recurring objections or timing signals and use those outcomes to improve subsequent runs.
That turns the product thesis from: “automate this GTM task into learn which GTM action should happen next”.
Clay calls the result a self-learning revenue engine.
Clay is also building the profession around the platform
There is another layer to the financing that is easy to overlook.
Clay is committing $1 million to scholarships for GTM Engineers, a role that sits between growth, revenue operations, automation and software-style systems thinking. The company says thousands of people are already working in the emerging discipline.
That creates an ecosystem strategy alongside the product strategy.
Clay develops the infrastructure. GTM Engineers learn how to build revenue systems on top of it. Companies then hire people with those skills, increasing the number of organizations capable of deploying Clay more deeply.
The Series D therefore arrives at a transition point. Clay has already shown that businesses will pay for programmable GTM infrastructure. The harder question is whether agents can reliably learn from commercial outcomes rather than merely execute increasingly sophisticated instructions.
If Clay can make that feedback loop work at enterprise scale, the $115 million will be funding something larger than another generation of sales automation.
It will be funding an attempt to make go-to-market itself adaptive.