$700M/year Sacra for public markets
Jan-Erik Asplund
TL;DR: Where Bloomberg and FactSet organized the structured data of markets, AlphaSense built search over the unstructured layer of filings, transcripts, broker research & expert calls, then acquired its way from licensing that content to owning it. Now, on the back of AI search, Sacra estimates AlphaSense hit $700M ARR in June 2026, up from $540M at the end of 2025, valued at $7.5B for a 10.7x multiple as it explores an IPO. For more, check out our full report and dataset on AlphaSense.
Key points via Sacra AI:
- With equity analysts spending days researching companies across Bloomberg, EDGAR & scattered PDFs, AlphaSense (2011) launched as a search engine for investment analysts to run queries like "smartphone component margins" and instantly pull results across all filings, earnings transcripts, presentations, and press releases. At $12K–$15K/seat/year, AlphaSense prices low enough such that it can be supplementary to the $30K/year Bloomberg terminal used by its hedge fund & bank analyst customers, while also opening up the market of corporate strategy, corp dev & IR teams that want equities research but don’t need Bloomberg’s live prices & chat.
- Starting with aggregating information from public filings & the open web, AlphaSense moved into more and more proprietary content, licensing broker research from 1,700+ providers via Wall Street Insights (2020), then acquiring Tegus for $930M in 2024 to capture its 200,000+ expert call transcripts and 4,500 Canalyst financial models, with Sacra estimating AlphaSense hit $700M ARR in June 2026, up from $540M at the end of 2025, growing 40% YoY, and valued at $7.5B for a 10.7x multiple. Compare to FactSet (NYSE: FDS) at $2.44B in TTM revenue, up 6.4% YoY, valued at $10.1B for a 4.2x multiple, Morningstar (NASDAQ: MORN) at $2.51B in TTM revenue, up 8.4% YoY, valued at $7.8B for a 3.1x multiple, and Perplexity at $500M in annualized revenue in April 2026, up 335% year-over-year, valued at $20B as of their September 2025 E for a 100x multiple on ~$200M revenue.
- The switch from keyword search to AI search & agents especially favors AlphaSense’s rich unstructured data repository, deepening its potential as the answer engine destination for strategy, investing & finance customers and driving a data flywheel where proprietary data sources generate user engagement and proprietary usage data that deepens its non-public data moat. Meanwhile, FactSet, S&P Capital IQ, Morningstar, CB Insights & PitchBook are integrating, licensing and partnering with ChatGPT, Claude & Perplexity, monetizing their data inside the horizontal AI tools customers are already using and buying them time to deepen their AI search & agent experiences.
For more, check out this other research from our platform:
- AlphaSense (dataset)
- VP of Product at iCapital on streamlining alternative investment administration
- Product Marketing Leader at AlphaSense on the evolution of AI-powered financial research
- Managing Director at iCapital on wirehouse distribution challenges and tech evolution
- Engineering leader at Tegus on building a data platform for expert interviews
- SVP of Technology & Product Strategy at FactSet on driving trust through auditability
- Sr. Customer Operations Leader at Tegus on the Costco model of investment research
- Managing Director at iCapital on how evergreen funds are eating private market share
- Perplexity (dataset)
- Perplexity Computer vs Claude Cowork
- Perplexity at $148M/year
- Perplexity at $100M ARR
- Hebbia (dataset)
- Danny Wheller, VP of Business & Strategy at Hebbia, on vertical vs horizontal enterprise AI
