If you've ever wondered what junior bankers do all weekend, the answer is usually formatting PowerPoint slides and cross-checking numbers in Excel. It's the kind of grunt work that makes people question their life choices around 2 a.m. on a Saturday.
Model ML thinks it has a better solution. The AI workflow automation platform announced on Nov. 24 that it raised $75 million in Series A financing to automate the document creation process that keeps entire deal teams trapped in spreadsheets and slide decks. The funding comes remarkably fast—just six months after its seed round and only 12 months after the company launched.
FT Partners led the financing round, with participation from Y Combinator, QED Investors, 13Books, Latitude, and LocalGlobe.
The Problem: Millions Lost to Manual Formatting
Brothers Chaz Englander and Arnie Englander founded Model ML 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 sources, maintaining exact prior formats.
Here's the thing: pitch decks, investment memos, and diligence reports still require painfully 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.
"Analysts spend entire weekends cross-checking numbers and formatting slides," Chaz 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 recently put its verification workflow to the test against consultants from McKinsey & Company and Bain & Company on real Word and PowerPoint outputs. The consultants needed over an hour to complete the task. The AI platform finished in under three minutes and caught more errors. That's not just faster—it's more accurate.
How It Actually Works
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. Think of it as having an extremely detail-oriented associate who never gets tired and doesn't make copy-paste errors.
"Model ML is setting a new standard for how financial institutions leverage AI to achieve superior client results," said Steve McLaughlin, founder and CEO of FT Partners. "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."
Serious Backing and Rapid Growth
The company has assembled an advisory board that reads like a who's who of financial services leadership. Former HSBC Holdings CEO Noel Quinn, former UBS Group Chair Axel Weber, and former Morgan Stanley (MS) Capital Markets Chair Saul Nathan all advise the company.
In less than one year, Model ML has grown its customer base to include several of the largest investment banks, asset managers, and consultants globally, including two Big Four accounting firms. Clients include Lightspeed Venture Partners and Three Hills Capital. The company has also formed exclusive partnerships with S&P Global Market Intelligence and Crunchbase to power AI-driven insights across private market data.
"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.
The company plans to build dedicated onboarding and customer success teams in San Francisco, New York, London, and Hong Kong to support rapid enterprise adoption. When you're promising to eliminate weekend work for junior bankers, you'd better have good customer support.
