I’m Lok Kan, founder and CEO of FinCatch. We built FinCatch Studio for investment professionals who spend too much time moving between filings, earnings-call transcripts, news, and spreadsheets to answer research questions. Many AI research tools retrieve passages from individual documents. FinCatch Studio is designed to add the missing context: a financial knowledge graph that connects companies, people, filings, earnings transcripts, market events, and related concepts. That means you can do more than search for a mention. You can explore the relationships behind it and trace insights back to their source material. For example, rather than manually reviewing multiple documents to understand a company’s exposure to a supplier, executive change, sector trend, or material event, FinCatch Studio helps surface the relevant connections and supporting context in one research workflow. FinCatch Studio helps investment teams: - Research companies, sectors, and investment themes in one place - Ask questions across connected financial information - Explore relationships between entities, disclosures, events, and market context - Produce clear, source-backed insights more efficiently Our aim is not to replace investor judgement. It is to reduce the time spent gathering and connecting information, so investors can spend more time developing differentiated views. We’d especially value feedback from analysts, fundamental investors, research writers, and AI-agent builders. For those using agentic research workflows, what is missing when an agent can retrieve document snippets but has no financial relationship knowledge graph to traverse, connect evidence, and perform multi-step reasoning across entities and events? Thanks for taking a look at FinCatch Studio.

FinCatch Studio

AI research for connected financial insights

AI research for connected financial insights