Najnowsze wiadomości general: Tech.eu informuje o London and New York-based Model ML raises $75M

{'type': 'text/html', 'language': None, 'base': '', 'value': 'An AI automation platform for the financial services industry, founded by two brothers, has raised $75m in a Series A funding\xa0round.The funding round in London and New York-based Model ML was led by\xa0FT Partners with participation from Y Combinator,\xa0QED, 13Books, Latitude and LocalGlobe.The Series A follows six months after Model ML’s seed raise, led by LocalGlobe, and twelve months after its launch.Founded by brothers and repeat entrepreneurs Chaz and Arnie Englander, Model ML\xa0is leveraging AI so that financial services firms can work more efficiently..In particular, it says its tech enables financial teams to build AI workflows that automate repeat work,\xa0helping speed up compiling\xa0pitch decks and\xa0diligence reports\xa0as well as\xa0investment memos.\nThe platform slots into existing workflows, only pulling and processing data from a company\'s bank of trusted sources.\nModel ML says its\xa0platform is akin to building a bespoke AI brain for each organisation, and each AI agentic system is custom-built for individual clients.\nThe startup\xa0says its tech is used by several of the world\'s largest banks, asset managers and consultancies, including two of the Big Four accounting firms.The funding will be used to propel global expansion and beef up its AI capabilities across key financial hubs, it saidChaz Englander said: "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."'}