LinqAlpha Raises US$22 Million For Finance AI With Asia Backers

LinqAlpha raised US$22 million in Series A funding for its finance-focused AI platform, a round the startup framed as matching where much of its client demand already sits, e27 reported.

In the interview, the New York-headquartered startup outlined intelligence tools for institutional investors.

It identified AVP, Atinum Investment and GFT Ventures as anchor backers, alongside an Asia-heavy syndicate that included SV Investment, Mirae Asset, Samsung Securities and East Ventures.

LinqAlpha Names US$22 Million Series A And Asia-Heavy Backers

According to e27, Jacob Choi, Subeen Pang, Jin Kim and Hojun Choi founded LinqAlpha.

The source described the founding team as former Goldman Sachs analysts and MIT computer science PhDs, while LinqAlpha indicated that its client base already includes more than 70 financial institutions across the US, Europe and Asia.

In comments to e27, LinqAlpha stated that buy-side clients including Causeway Capital Management and Schonfeld Strategic Advisors collectively manage over US$5 trillion in assets.

Those figures remain company-attributed in the interview, not independently audited customer or revenue data.

Jin Kim, LinqAlpha's co-founder and head of forward deployed engineering, told e27 that roughly half the company's revenue comes from Asia Pacific.

He added that the startup runs New York for business development, Seoul as its product and engineering hub, subsidiaries in Hong Kong and Singapore, and London as the next planned market.

Financial Institutions Use Claims Remain Company-Attributed

Kim described client depth to e27 as daily workflow use, account expansion and integration depth.

His examples included morning briefings, alerts, meeting-preparation agents, multi-seat deployments and clients moving from the application to API access.

The platform is presented as a multi-agent system for research teams rather than a general search tool.

Kim explained that LinqAlpha builds a permissioned knowledge layer around each firm's internal research, thesis history and mandate, with agents reasoning across equities, macro, credit and foreign exchange.

Elsewhere, the interview positioned LinqAlpha against Bloomberg, LSEG, AlphaSense, Hebbia and Rogo.

Its argument was narrower: generic AI tools can give similar answers to similar users, while the product is intended to adapt to each institution's private context.

Security Claims Centre On Permissioned Data And Audit Trails

For the platform's outputs, LinqAlpha told e27 that every claim is grounded in licensed and vetted data with a citation back to source.

Kim noted that numbers are computed through code rather than generated by a language model, and that the startup runs multiple frontier models to reduce individual model bias.

That security section remained limited to company claims.

LinqAlpha maintained that each firm's notes, theses and research remain siloed, do not train shared models and do not cross accounts.

For institutions requiring stricter control, it added that API and MCP deployment patterns can keep agents operating inside the client's own environment.

On Asia coverage, Kim told e27 that the platform analyses 20,000+ companies across 80+ markets in 20 languages.

He added that clients already track Chinese-, Korean- and Japanese-language sources, with the same architecture extending across Southeast Asia.

Revenue, Accuracy And Contract Evidence Remain Undisclosed

The interview provides a funding number, named investors and named customer examples, but most operating proof remains company-supplied. e27 did not include audited revenue, contract values, retention rates, independent model-accuracy tests, pricing, security-review documents or a timetable for the planned London office.