Scend Ai

Scend is an AI-native research platform aimed at M&A workflows in private markets, using agentic search across databases, websites, maps, and directories to surface companies, buyers, and investors that static providers tend to miss. The product is built for private equity firms, buy-side origination firms, investment banks, corporate development teams, and other advisory groups , with additional traction among consulting and go-to-market teams that need to segment fragmented markets or map long-tail operators. For each cell in a dataset, Scend finds the source documents, extracts and structures the answer, and links back to supporting evidence , which matters for deal teams that need to defend a target list or investment thesis. The launch positions Scend as data infrastructure rather than another vertical SaaS tool, exposing the same agentic pipeline through an API and CRM integrations so firms can enrich existing pipelines instead of migrating off them. Typical jobs the platform handles include running a search for buyers, developing an investment thesis, building company profiles, and finding relevant conferences, all driven by a natural-language description of the thesis. The timing lines up with a broader shift in private markets, where teams that once paid for static databases are testing whether live web retrieval can cover niche, service-based industries that Pitchbook and similar tools underrepresent. Scend was co-founded by Yijie Feng, co-founder and CTO , previously an engineer at Robinhood, alongside CEO Anirudh Sathya, who earlier co-founded Teamwork Healthcare. The company is backed by Pear VC and has early customers on the platform , and is hiring founding engineers in New York as it expands coverage across investor, advisor, and corporate development workflows.