Dataglade is an AI-native equity research platform that aims to be the smart way to research stocks. It uses AI to generate clear, structured analyses and full financial models for any public company, automating much of the time-consuming work that fundamental analysts perform when building models and forming investment views. The goal is to compress hours of spreadsheet and document work into fast, queryable research that analysts can trust.
A defining feature of Dataglade is traceability: every number the platform produces is backed by citations to proprietary financial data, so users can see exactly where each figure comes from. In professional investing, where decisions move large sums and must withstand scrutiny, this citation-first design addresses the core trust problem with generative AI. Rather than asking analysts to take AI output on faith, Dataglade makes its analyses auditable, letting users verify the underlying data behind every model assumption and conclusion.
The platform serves analysts, portfolio managers, and traders who need to evaluate public companies quickly and defensibly. By generating financial models and analyses on demand, Dataglade helps research teams cover more names, refresh models faster, and surface insights without rebuilding spreadsheets from scratch. The company states that its outputs inform more than $1 billion of trades every day, indicating meaningful adoption among active market participants who rely on its analysis as part of their decision process.
Dataglade is a venture-backed startup in the AI finance and trading-research space, listed among Y Combinator's finance companies. It competes in the fast-growing category of AI financial research tools alongside platforms building AI investment analysts and research copilots. As institutional and professional investors increasingly adopt AI to accelerate fundamental research while demanding verifiable outputs, Dataglade's citation-backed model-generation approach positions it to serve trading and investment teams that need both speed and defensibility in their analysis.