Databento Raises $100M for Market Data and AI Demand

The next customer for a trading-data feed may be building an AI system. At Databento, that widening demand is pulling a company founded by quantitative-finance practitioners toward a faster expansion of the physical infrastructure behind its APIs.

The Salt Lake City company announced a $100M Series C on November 12, 2026, at a $1.1B valuation. Fifth Down Capital led the financing, and Fitch Ventures joined as a strategic investor. The money supports more market-data infrastructure and coverage of additional asset classes, extending a business that serves trading firms, brokerages, asset managers and increasingly AI developers.

Co-founder and CEO Christina Qi says Databento was already profitable and was not actively seeking another round. Customers wanted a faster expansion, while existing investors wanted larger commitments. That puts a useful question inside the transaction: how much of a data supplier's growth timetable should follow the needs of people building on its records?

A returning investor helps accelerate the timetable

Fifth Down Capital invested before Databento generated revenue and has now moved into the lead position. In the company's financing release, Fifth Down founder and CEO Andrew Spellman points to institutional adoption, growth and profitability as reasons for increasing its involvement. His account describes the investor's conviction, rather than providing an independent audit of the business.

Fitch Ventures adds an investor connected to the financial-information industry. Gabby Munoz, Fitch Group's global head of M&A and venture investments, frames the opportunity around financial data becoming increasingly API-driven and consumed by machines. The strategic investment connects two businesses concerned with the delivery and use of financial information; the announcement does not disclose a distribution agreement between them.

The company also names follow-on investments from NEA, DRW Venture Capital, Tribe Capital, Redpoint Ventures, Hedosophia, Trousdale Ventures, Cross Creek, Operator Collective, Alumni Ventures and TGVP. This is a financing with considerable continuity in its backing, alongside a new strategic participant.

Only four months separate this announcement from Databento's $97M Series B, announced on July 9 and led by NEA. The company says revenue has more than doubled since that round while it remains profitable. Absolute revenue and audited financial statements are not supplied, so the growth figure establishes the company's reported direction without revealing the size of its revenue base.

The API moves work toward the supplier

Databento provides real-time and historical data across futures, options, equities and indices. Its technical documentation describes a platform offering normalized data and raw packet captures, giving developers different ways to work with financial-market records. The customer can begin with an interface rather than assembling every part of a feed-delivery system.

That convenience carries an operating assignment. Someone still has to capture market activity, process large volumes of records and keep the delivery infrastructure running. A developer can access the resulting data through software while depending on physical equipment and engineering work that remain outside the application being built.

Databento's schemas and data formats make the abstraction more concrete. Consistent representations help an application consume information from different sources. For an engineering team, the commercial value can include less time spent reconciling incompatible inputs before it can begin answering the question that motivated the purchase.

That is an interpretation of the product's usefulness, not a measured saving promised to every customer. Teams still have to choose appropriate datasets, understand the records they receive and build applications that use them correctly. A cleaner access path changes the division of work between customer and provider, with the provider carrying more of the repeated infrastructure task across its customer base.

AI demand widens the audience for precise records

Databento says it has signed enterprise contracts with five of the six leading frontier AI labs. The company does not name those labs in the funding announcement, identify the contract values or explain how their usage contributes to revenue. Its claim nevertheless helps explain why the financing discussion now reaches beyond the company's roots in institutional trading.

An AI developer and a quantitative trading team can approach the same data with different applications in mind. Both have reason to care about what a record represents and how it was captured. As more software consumes the feed, the quality of the underlying financial information becomes part of work happening farther from the original trading venue.

Christina Qi and co-founder Luca Lin built Databento after working in quantitative finance. Their current company biographies connect both to Domeyard, while investor Operator Collective's founder profile describes the costly process of finding, cleaning and onboarding datasets that informed the business. The product's developer orientation grows out of that practical experience.

The widening audience also changes how an operator should read the expansion plan. Another asset class can create opportunities for existing financial customers and for software teams whose needs were not central to the provider's original market. Whether those groups become equally valuable customers will depend on their actual usage, service requirements and economics, none of which the financing announcement breaks out.

A small team is expanding a physical footprint

Databento closed the Series C with 39 employees, according to its release. The company blog says infrastructure buildouts at nine data centers are nearly complete, naming sites across Australia, Asia and Europe as well as the US. That wording describes progress in an expansion, rather than nine newly operating facilities or a verified total network count.

The longer ambition is a larger commercially available historical market-data archive, ultimately the largest in the company's stated plan. Broader historical coverage could give a developer more periods and markets to examine, while additional infrastructure supports the work of capturing and distributing those records. The ambition remains a goal, with considerable operating work between the announcement and its completion.

The funding gives Christina Qi and Luca Lin more resources to bring coverage forward. When that coverage reaches a developer, the expansion plan becomes a choice about which market or period to study next. Databento will be selling a wider set of questions that can be asked of the same API, with the customer's next research idea waiting on the other side.