Accern

Accern provides a no-code, artificial intelligence platform that enables enterprises to extract actionable insights from unstructured data. Founded in 2014 by Kumesh Aroomoogan and Anshul Vikram Pandey, the New York-based company specializes in Natural Language Processing (NLP) solutions primarily for the financial services industry. Aroomoogan’s experience at Citigroup, where he witnessed the manual and labor-intensive processes of data analysis, inspired the creation of Accern to automate these tasks. He partnered with Pandey, who was a data visualization Ph.D. student at NYU at the time, to build the company.

The company's main offering is a platform that allows users, including those without a technical background like business analysts, to build and deploy AI and NLP models. The platform provides tools to analyze vast amounts of content from sources like news, social media, regulatory filings, and internal documents to inform investment decisions and manage risk. Its solutions cover use cases such as equity research, credit risk, ESG performance, fraud prevention, and M&A activity. The platform includes pre-built models and a marketplace with over 400 financial service application templates to accelerate deployment. The business model is subscription-based, with pricing tiers based on the volume of data processed. Its clientele includes hedge funds, asset managers, banks, and insurance companies, with names like Mizuho Bank, Allianz, and Capgemini mentioned as customers.

Accern has raised approximately $40 million in funding over several rounds. Key funding milestones include a $13 million Series A in 2020 and a $20 million Series B in 2022. Investors include Fusion Fund, Mighty Capital, Tribe Capital, and Shasta Ventures. In February 2025, Accern was acquired by Wand AI, a startup specializing in AI agents, for a price reported to be in the eight-figure range. This acquisition aims to integrate Accern's financial data aggregation and AI capabilities into Wand AI's platform to enhance its AI agents for the financial sector.

Keywords: no-code AI, natural language processing, NLP, financial services, unstructured data analysis, AI-powered insights, investment research, risk management, automated workflows, data analytics platform, fintech, machine learning, equity research, credit risk, ESG analysis, fraud detection, M&A analysis, alternative data, financial news surveillance, asset management