Problem

Dataglade addresses the time, fragmentation, and verification burden involved in investment research. Investors and analysts traditionally have to dig manually through financial filings and disparate market datasets, a process that consumes hours every day and can cause important insights or alpha opportunities to be missed. The economic pain is therefore both analyst productivity and the quality and speed of decisions informing trades.

The killer use case is on-demand research for a public company or peer group: an investor can ask a question, compare companies, generate an analysis, or build a financial model without manually assembling the underlying evidence. Dataglade’s examples include analyzing Palantir’s product categories and comparing the strengths and weaknesses of the top U.S. REITs, while its reports link numbers and conclusions back to source data for validation.

Product / Service

Dataglade is an AI-powered financial research terminal and data platform. Its coverage includes real-time fundamentals, ratios, multiples, comparables, earnings, analyst estimates, options activity, insider trades, and other market data across more than 48,000 companies, 30-plus asset classes, and 20-plus geographies. Its AI works across more than one million financial filings and can produce company analyses, memos, SWOT or other structured frameworks, and complex financial models. Source-linked numbers and citations to filings, earnings calls, and news are intended to make the output both fast and auditable.

The delivery model combines an online terminal and app experience with sales-assisted institutional offerings. Hedge funds, wealth managers, fintechs, banks, consultants, and other research users can access the shared market-data platform, while firms can also securely connect structured or unstructured internal data to generate proprietary insights and custom dashboards. The benefit is a faster research workflow with broad data coverage, live market context, and less manual document review, while preserving the ability to check the evidence behind an answer.

Market

Dataglade competes in fintech and generative-AI software, specifically the AI-powered financial research, market-intelligence, and equity-research-terminal categories. Its closest substitutes include established financial information terminals and research platforms such as Bloomberg Terminal, FactSet, AlphaSense, LSEG Workspace, S&P Capital IQ Pro, Morningstar Direct, PitchBook, and newer AI research products such as Hebbia. Dataglade’s positioning is to combine broad structured financial data with generative analysis rather than sell only a conventional data terminal or only a document-search tool.

The company appears to be an active but very small early-stage business rather than pre-revenue on the available evidence. Dataglade’s website says hedge funds, wealth managers, and fintechs trust it to inform more than $1 billion of trades each day, although that is a company claim rather than independently audited usage data. Y Combinator lists it as an active Winter 2023 company founded in 2022 with a two-person team, while Tracxn reports that it has not raised funding. A third-party Latka estimate puts 2025 revenue at $440,000, so the best-supported characterization is early commercial traction with limited disclosed scale, not confirmed pre-revenue status.