Bigdata.com

Bigdata.com is the AI grounding layer for finance — it stops agents from hallucinating by grounding every answer in real, cited sources instead of guesses. Ask in plain language and get back cited, source-linked answers instead of a wall of raw data to parse yourself.

Query stocks, market data, portfolio holdings and fundamentals alongside SEC filings, earnings calls, broker and analyst research, press releases, and sentiment signals across billions of documents spanning 25+ years: 10M+ new public news documents monthly, 200+ premium news sources (Financial Times, Benzinga, MT Newswires and more), filings across 50+ countries, 30+ years of fundamentals, expert interviews, and podcasts.

RavenPack's financial knowledge graph resolves company and entity names automatically, so a single query surfaces the right filings, transcripts, and news without manual ticker-matching. Every claim traces back to a real, citable source — no fabricated numbers, no invented quotes.

Beyond public content, search and upload your own private documents — notes, research, and internal files — side-by-side with public filings and market data, so proprietary research and public sources answer from the same query.

Because retrieval returns only the cited excerpts that matter instead of stuffing whole documents into context, typical queries use around 90% fewer input tokens than an ungrounded approach.

Built for anyone making a financial decision — from individual investors sizing up a trade to analysts at hedge funds, asset managers and investment banks. Run an initiation report, compare two 10-Ks, prep a pre-earnings or pre-FOMC briefing, track a competitor, catch a sentiment shift before consensus does, or build a sourced brief before a call — all from one grounded search.

Connect in seconds inside Claude — no setup, no glue code. You're searching cited financial data from your first prompt.