AI workflow automation platform Model ML announced on Nov. 24 that it raised $75 million in Series A financing to eliminate the formatting grunt work that haunts junior bankers. The funding comes just six months after its seed round and only 12 months after launch.
The company aims to replace manual document creation that keeps entire deal teams trapped in spreadsheets and slide decks. FT Partners led the financing round, with participation from Y Combinator, QED Investors, 13Books, Latitude, and LocalGlobe, according to Model ML.
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Brothers Target Financial Services Inefficiency
Chaz Englander and Arnie Englander founded the company to transform how financial institutions handle high-stakes deliverables. The platform enables financial teams to build AI workflows that automate client-ready Word, PowerPoint, and Excel outputs directly from trusted data in exact prior formats.
“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,” Chaz Englander said in the company's statement.
Platform Targets Manual Processes Costing Banks Millions
Pitch decks, investment memos, and diligence reports still require slow, manual processes that strain teams and stall business momentum. Deal teams across all seniority levels lose time formatting outputs and chasing inconsistencies across Word, Excel, and PowerPoint, according to Model ML.
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“Analysts spend entire weekends cross-checking numbers and formatting slides,” Englander said in the company's statement. “Despite all that effort, mistakes still slip through because no one can realistically verify every data point in a 100-page deliverable.”
Model ML said it recently tested its verification workflow against consultants from McKinsey & Company and Bain & Company on real Word and PowerPoint outputs. The consultants required over one hour to complete the task, but the AI platform finished in under three minutes and caught more errors.
The platform’s agent workflows interpret schemas, reason across multiple sources, write code to extract or transform data, and generate finished branded outputs with verification built in.
“Model ML is setting a new standard for how financial institutions leverage AI to achieve superior client results,” FT Partners founder and CEO Steve McLaughlin said in Model ML's statement. “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.”
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Rapid Enterprise Adoption Across Financial Services
The company’s advisory board includes former HSBC Holdings CEO Noel Quinn, former UBS Group Chair Axel Weber, and former Morgan Stanley (NYSE:MS) Capital Markets Chair Saul Nathan, according to Model ML.
In less than one year, the company said it has grown its customer base to include several of the largest investment banks, asset managers, and consultants globally, including two Big Four accounting firms.
Model ML has attracted clients including Lightspeed Venture Partners and Three Hills Capital, and has formed exclusive partnerships with S&P Global Market Intelligence and Crunchbase to power AI-driven insights across private market data, according to the company website.
Model ML said it will build dedicated onboarding and customer success teams in San Francisco, New York, London, and Hong Kong to support rapid enterprise adoption.
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