Model ML announced a $75 million Series A round led by FT Partners, marking a major capital infusion for the AI workflow automation startup serving financial institutions. The financing which includes participation from Y Combinator, QED, 13Books, Latitude and LocalGlobe follows the company’s seed round just six months earlier and arrives roughly a year after Model ML’s market debut.
“We’re thrilled to announce this round with such an exceptional group of investors as we continue our mission to transform how financial institutions work. This financing enables us to accelerate global expansion and advance our AI capabilities across key financial hubs as we scale to meet rapidly growing enterprise demand,” said Chaz Englander, CEO of Model ML. “We couldn’t imagine a better strategic partner for us than FT Partners – Steve McLaughlin and his team have long been pioneers in leveraging data and technology in investment banking, and our tight collaboration will show how AI can redefine the entire financial advisory workflow.”
FT Partners’ Steve McLaughlin added backing for Model ML’s potential to reshape client workflows: “Model ML is setting a new standard for how financial institutions leverage AI to achieve superior client results,” he said. “While we expect significant efficiency gains, the true power of Model ML lies in the insights it will unlock for our clients, investors, and the broader FinTech ecosystem. We believe Model ML will fuel the next evolution of world-class service for our clients and transparency across all stakeholders in transactions.”
Founded by brothers Chaz and Arnie Englander, Model ML builds AI “agents” that produce client-ready Word, PowerPoint and Excel deliverables directly from verified data and in exact prior formats. The platform is already used by several of the world’s largest banks, asset managers and consultancies, including two Big Four firms.
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High-stakes outputs pitch decks, investment memos, diligence reports are traditionally created through slow, error-prone manual workflows. Model ML’s agentic automation interprets schemas, extracts and transforms data, and generates finished, branded documents with built-in verification. In one benchmark, Model ML completed a verification task in under three minutes and found more errors than consultants from McKinsey and Bain, who required over an hour.
“High-stakes business runs on documents: pitch decks, diligence summaries, investment memos. But most firms still build them the hard way. Analysts spend entire weekends cross-checking numbers and formatting slides. Despite all that effort, mistakes still slip through because no one can realistically verify every data point in a 100-page deliverable. That’s why we built Model ML. Our agents reason across data sources, write the code to extract and transform what’s needed, and generate finished, branded outputs with verification built in. We’re eliminating the grunt work so teams can focus on the analysis that actually matters,” Chaz Englander said.
The new funding will accelerate international expansion and deepen Model ML’s enterprise features as financial institutions increasingly adopt AI to boost speed, accuracy and client-facing insight delivery.
