Metal, a New York-based artificial intelligence startup that transforms how private equity firms analyze investment opportunities, has raised $5 million in funding led by Base10 Partners to build what it calls the first AI operating system for private markets.

The funding round, which closed in June, represents a significant vote of confidence in Metal's approach to solving one of private equity's most persistent challenges: making sense of vast amounts of fragmented data scattered across multiple systems during the investment decision-making process.

"We always look at software from a data and infrastructure perspective first — how everything needs to relate within a single system," said Taylor Lowe, Metal's co-founder and CEO, in an exclusive interview with VentureBeat. "This framing is essential to addressing the core problem in private markets. It's what has enabled us to transform years of firm knowledge into a living intelligence system that amplifies judgment and accelerates decision-making."

How private equity firms waste millions on manual data analysis

The challenge Metal addresses is both universal and expensive in private equity. Investment teams routinely juggle information from expert call transcripts, SEC filings, financial statements, board presentations, and confidential information memorandums — often spending days manually parsing documents that could inform critical investment decisions worth hundreds of millions of dollars.

"Deal teams are overloaded with data, yet competitive deals are lost due to inefficient diligence processes," Lowe explained. "In early diligence alone, analysts spend days reading through expert call transcripts, 10-Ks, or financial statements just to get a basic understanding of a company. This is a highly manual process — and funds are paying analysts $200,000 or more per year to do it."

Metal's solution centers on what Lowe describes as a "data-first and infrastructure-first approach" that aggregates all of a fund's historical investment data — memos, expert calls, management meetings, and financial documents — into a single, searchable system. The platform then uses large language models to extract insights and generate analysis while maintaining strict source attribution for compliance purposes.

Why Metal pivoted from general AI platform to private equity specialist

Metal's journey reflects the broader evolution of AI applications in enterprise settings. The company, founded by former executives from Meta, Carta, Spotify, and other tech companies, initially launched as a general-purpose developer platform for building AI applications with large language models.

However, early work with Berkshire Partners, one of Metal's first customers and still a client today, revealed the specific challenges facing private equity firms. "We made a decision later that year to really go all in, and then we launched the application on top of the infrastructure at the start of 2024," Lowe said.

The pivot proved prescient. Unlike broad-based research platforms such as CB Insights or PitchBook that serve multiple market segments, Metal focuses exclusively on the diligence lifecycle within private equity. This specialization allows the platform to integrate deeply with each fund's specific investment frameworks and decision-making processes.

"Each fund has its own approach," Lowe noted. "At a high level, the private equity process might seem uniform, but when you look closely, it's quite different — even down to how each fund creates its diligence work products like one-pagers, market research reports, or investment committee memos.”

Private equity giants boost deal flow 300% with Metal's AI platform

Metal's customer base includes established private equity firms such as Berkshire Partners, Clearlake Capital, and Blue Wolf Capital. The results, according to Lowe, have been significant: some customers have increased their inbound deal flow by 200% to 300% without adding headcount by automating the initial data capture and scoring of new opportunities.

"Some funds of ours have said, 'Whenever we get a new inbound opportunity, we're just going to say yes to it now, because we can actually automatically extract all the key data points that we care about as a fund,'" Lowe explained. "We can take those extracted values, run them through a scoring framework that they would use internally, and do that basically at marginal cost."

Eric Souza, CTO at Berkshire Partners, emphasized the partnership aspect of Metal's approach: "With Metal, we've fast-tracked our path to leverage meaningful AI benefits across the firm — from our investment staff to our support staff. Metal's partnership-driven approach has been key — not only in implementing the technology but in ensuring its adoption across our firm."

Building an institutional brain: How Metal digitizes decades of investment knowledge

Perhaps Metal's most significant value proposition lies in what Lowe calls building an "institutional brain" for investment firms. By digitizing and structuring decades of investment history, the platform enables partners to query their firm's collective knowledge in ways previously impossible.

"We're seeing funds upload their entire investment history — millions of files — onto the platform, and then deal team members can simply ask questions through chat, generate reports, and create diligence work products," Lowe said. The more firms use the platform, he added, the more valuable it becomes as new data feeds back into the system.

This approach addresses a crucial insight: "The average Metal customer uses 80% to 90% internal data to make investment decisions — data that is fundamentally unique to them," Lowe explained. "Those insights from that data are unique to them, and we're a system that can basically store and extract that information at scale."

Enterprise-grade security meets AI: Metal's technical approach to sensitive financial data

Metal's technical approach differs significantly from competitors by prioritizing data infrastructure over user interface. The platform starts with purpose-built ingestion pipelines for financial documents, then structures the data to support the complex relationships between companies, sectors, and investment themes that drive private equity decision-making.

Security remains paramount given the sensitive nature of private equity data. Metal maintains SOC 2 compliance, uses only enterprise APIs that don't train foundational models with customer data, and employs multi-tenant architecture that prevents data sharing between customers.

"We handle a lot of sensitive data in the platform," Lowe acknowledged. "There's no model training or any sort of leaving of the data to feed back to a foundational model. That's never the case with us."

Base10 Partners leads $5 million round as AI transforms private markets

The $5 million round led by Base10 Partners reflects growing investor interest in AI applications for financial services. Rexhi Dollaku, General Partner at Base10 Partners, noted the broad market opportunity: "Everyone wants a solution like Metal, whether they know it yet or not, and we expect many funds will begin to realize they won't be able to move forward as top-quartile funds without it."

The funding follows Metal's earlier $2.5 million round raised in 2023, bringing total funding to $7.5 million. The company plans to use the new capital to expand its engineering, sales, and marketing teams while deepening its partnerships with existing customers.

The competitive advantage of AI infrastructure in private equity's future

Metal's strategic vision extends far beyond automating document review. The company is building toward what Lowe describes as a comprehensive system of record for private equity — one that captures intelligence throughout the entire investment lifecycle, from initial deal sourcing through portfolio monitoring and eventual exits.

"Every single transaction starts with diligence," Lowe explained. "If you're going to want to capture and build a system of record that the fund can then learn from and compound its insights on top of, that is where you want to start."

This infrastructure-first approach may prove decisive as artificial intelligence becomes table stakes in private equity. While competitors focus on flashy user interfaces or broad market coverage, Metal is quietly building the data foundation that could power the next generation of investment decision-making tools.

The implications reach beyond operational efficiency. In an industry where information advantages often determine which firms win the most attractive deals, Metal's approach to institutionalizing knowledge represents a fundamental shift in how private equity firms can compete. The winners may not be the firms with the largest teams or the most capital, but those with the most sophisticated AI infrastructure.

As Lowe put it: "I think for folks that choose to invest wholeheartedly in AI now, those are the types of returns that they're setting themselves up for, because you want to collect as much of that data as possible, and you want to do so on an ongoing basis."

The question for private equity firms is no longer whether AI will transform their industry, but whether they'll build the infrastructure to lead that transformation — or get left behind by those who do.