Problem

Investment research is fragmented across company filings, live market data, macroeconomic indicators, trade statistics, and other specialized sources. A question about a ticker rarely stays limited to the company: a margin question can lead to commodity prices, while a guidance question can require demand or trade data. The pain is therefore both workflow friction and analytical reliability—analysts spend time navigating portals, reconciling units, frequencies, definitions, revisions, and provenance instead of testing an investment thesis.

The killer use case is an end-to-end, source-traceable research workflow. An analyst or AI agent can move from company fundamentals and valuation to relevant market, macro, and trade indicators—for example, connecting a semiconductor company's results with memory exports—without stitching together multiple data vendors or manually validating every number.

Product / Service

FactIQ is a data layer and plugin for AI agents that combines standardized company financials, live and historical market prices, macroeconomic and trade series, and selected geospatial data. The agent queries FactIQ directly, performs calculations in its own context, and publishes the resulting analysis as shareable charts and reports with each number traced back to its source. Behind the scenes, FactIQ normalizes disparate official datasets into a common schema so an agent can discover series and query different sources using consistent patterns.

The delivery model is agent-native rather than a conventional standalone terminal: FactIQ is available through coding-agent workflows and a ChatGPT connector. The product is currently offered free, with the public site advertising a forthcoming Pro plan at $49 per month and no query, chart, or seat limits in the free offering. Its benefit is faster research with broader context, more reproducible calculations, and clearer evidence trails.

Market

FactIQ competes in the emerging AI-native investment-research and financial/economic-data infrastructure market. Its positioning sits between traditional institutional data terminals and developer-oriented data APIs: it packages official financial and economic data for AI agents rather than requiring analysts or developers to assemble and normalize each source themselves. The adjacent competitive set includes Bloomberg Terminal, FactSet, LSEG, and AlphaSense, while newer AI-oriented research platforms such as Fiscal.ai address a similar investment-analysis workflow, although the reviewed sources do not establish that all of these are direct competitors.

FactIQ appears to be an early-stage, active company rather than a scaled incumbent. Y Combinator lists it as founded in 2023, part of Winter 2023, active, based in Singapore, and operating with a three-person team; its public product is live and continued data additions were announced in June 2026. Revenue, paying-customer counts, and funding were not disclosed in the reviewed sources. Because the product is advertised as free today with paid functionality still described as coming soon, it is best characterized as early commercial or pre-scale, but the evidence does not prove that it is literally pre-revenue.