AlphaSense vs Pagaya

AlphaSense has a disclosed valuation of $4B, while Pagaya's valuation is not publicly available, making a direct size comparison difficult. AlphaSense employs 1750 people.

AlphaSense has raised more in total funding at $1.4B, compared to Pagaya's $600M — a gap of $800M. Combined, the two companies have completed 7 known funding rounds.

AlphaSense leads with an Awaira Score of 82/100, while Pagaya sits at 70/100. That 12-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

AlphaSense was founded by Jack Kokko in 2011. Pagaya was founded by Gal Krubiner in 2016. Visit each company's profile on Awaira for a full founder biography.

AlphaSense: AlphaSense is an AI-powered market intelligence platform founded in 2011 that helps financial professionals extract actionable insights from vast amounts of unstructured data. The company's core product uses natural language processing and machine learning to analyze earnings calls, news articles, research reports, regulatory filings, and other financial documents in real-time. AlphaSense enables investment professionals, including hedge funds, asset managers, and institutional investors, to identify market trends, competitive threats, and investment opportunities faster than traditional research methods. The platform processes millions of documents across multiple languages and industries, allowing users to conduct semantic searches rather than keyword-based queries. AlphaSense has secured $1.4 billion in total funding and achieved a $4.0 billion valuation as of its Series F funding round, reflecting strong investor confidence in the enterprise AI market. The company competes with traditional financial data providers and emerging AI research platforms by offering superior automation and speed. Its customer base includes major financial institutions and hedge funds globally. AlphaSense's growth trajectory has been accelerated by increasing demand for AI-driven research tools among institutional investors seeking competitive advantages in information analysis and decision-making speed. AlphaSense combines specialized NLP for financial data with institutional-grade performance at scale, addressing a specific pain point in professional investment research. Pagaya: Pagaya operates an AI financial underwriting network that processes consumer loan applications on behalf of lenders, using machine learning models that evaluate creditworthiness across a broader set of data signals than traditional credit bureau scores, enabling lenders to approve more applicants while maintaining or improving default rates. The Tel Aviv and New York company monetises by taking a network fee on loan volume processed through its AI underwriting system, funded by institutional investors who purchase the approved loan pools.\n\nThe company went public on NASDAQ via SPAC merger, having raised over $600 million in combined public and private funding from investors including Oak HC/FT and Viola Growth. Pagaya reports processing hundreds of billions of dollars in loan applications annually across personal loans, auto loans, and mortgage products, with network partners including SoFi, Ally Financial, and US Bank embedded in its origination technology. The business model operates as an AI network sitting between lenders who originate applications and institutional investors who fund approved loans.\n\nPageya competes in the AI credit underwriting market against ZestFinance, Upstart, and traditional credit bureau scoring models from Fair Isaac. Its network model, where multiple lenders access the same AI infrastructure and their collective data improves model performance over time, creates compounding advantages compared to single-lender AI implementations. The company has navigated regulatory scrutiny around AI lending decisions and disparate impact as financial regulators increase oversight of alternative data use in credit decisions.

AlphaSense got there first, launching in 2011 — that's 5 years of extra runway. Pagaya didn't arrive until 2016. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

AlphaSense has about 1750 employees; Pagaya has about 500-1000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both AlphaSense and Pagaya compete in AI Finance, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.