risk-detection
(3)
AppliedXL
AppliedXL is a New York-based event-detection company that builds machine-learning systems - it calls them editorial algorithms - to spot early signals in clinical trials, biotech, and financial data before they become news. Founded in 2020 by former Wall Street Journal computational journalists Francesco Marconi and Erin Riglin out of the Newlab Venture Studio, the company mines public databases like ClinicalTrials.gov to flag trial delays, enrollment shortfalls, and irregular status changes across more than 100 risk categories, feeding real-time intelligence to life-sciences executives and investors. Its work powers STAT Trials Pulse and appears on the Bloomberg Terminal.
SQOR.ai
SQOR.ai is a New York-based, AI-native decision intelligence platform that replaces legacy business-intelligence complexity with a plug-and-play system. It connects read-only to 800+ data sources and SaaS tools a company already uses, unifies their KPIs, and deploys 60+ AI agents that apply machine learning for causation, prediction, and recommendation - so operators, funds, and their LPs can ask questions in plain language and get objective answers in minutes instead of quarters. Its proprietary Execution Score Algorithm (ESA) quantifies operational health at the tool, division, and company level.
Pienso
Pienso is a no-code AI platform that lets domain experts - not just engineers - train, fine-tune, and deploy their own machine learning and large language models without writing a single line of code. Founded by MIT Media Lab alumni Birago Jones and Karthik Dinakar, Pienso keeps humans in the loop and data in the customer's control, with cloud or on-premise deployment for governments, media companies, and regulated enterprises.