We're thrilled to announce that Multiplier has raised $6 million in seed funding, led by Peter Hebert of Lux Capital. Y Combinator, GoAhead Ventures, Rebel Fund, General Advance, Unpopular Ventures, Amino Capital, and CRV participated. So did Greg Jensen and Karen Karniol-Tambour (co-CIOs, Bridgewater Associates), Pete Briger (Chairman, Fortress Investment Group), Jasjeet Sekhon (CSO, DeepMind), Sandeep Nailwal (CEO, Polygon), Kaz Nejatian (CEO, OpenDoor), Henri Stern (CEO, Privy), and our customers.
This money will buy us the talent and tokens we need to make Multiplier the obvious choice for any AI-pilled investor. It's a bet that agents and human stockpickers are stronger together.
IN BRIEF
Investors are drowning in information. Filings, sell-side reports, expert calls, articles, substacks, podcasts, tweets, satellite imagery, channel checks, earnings calls, management interviews, conference notes, breaking news... To invest well, you need to filter, synthesize, and interpret this flood. Then you need to consider your own portfolio construction, investment philosophy, trading history, and edge to decide how to take a position—faster than the market, which gets faster every day. Behemoths like Bridgewater and Balyasny have seized AI to solve this problem, leaving independent funds further behind.
Other financial AI tools haven't closed this gap; they're disjointed point solutions without the power and generality of coding agents. Out-of-the-box coding agents lack the connectivity and specialization necessary to get real investment work done. Multiplier deploys coding agents with the tuning and infrastructure to help investors cover twice as many stocks twice as deeply. We're already live with five fundamental equity hedge funds.
That's the core of it, and it's a pitch you'll hear plenty. But this is our launch post, so we'd like to share our philosophy, methods, and ambitions.
WHY WE STARTED MULTIPLIER
Originally, we called our company "WithAI." Although better than "WithoutAI," the name didn't convey much. "Multiplier" encapsulates our philosophy: we don't aspire to "pick stocks with AI"; we're not making an "artificial investor"; instead, our platform multiplies great human investors. Agents handle simpler work (filtering articles, making charts, monitoring price action, updating memos, etc.), freeing users to double their breadth and depth of coverage. We don't expect mass unemployment from AI. We expect that in 2030, all white-collar labor will look something like this, with AI-powered mental exoskeletons making work several times more productive and challenging for every worker.
Ian McInnis was a stockpicker (and LLM investment system builder) at Bridgewater when he came to this conclusion. One night Ben Finch (founding researcher at AI unicorn Sentient) called him with a product idea, and Ian thought it fit perfectly. They added Ryan Winkler (investor at StepStone) to the call—at Princeton, we three had founded a consistently benchmark-beating hedge fund and became fast friends doing so.
We settled quickly on building for investors. It's not just that we know how investing works—investors are the most AI-augmentation-ready workers we could think of. Really! Not programmers. Claude Code with Fable 8 might wholly automate programming jobs, not augment them. But investors are paid to disagree with the market, to spot something others don't spot. Claude Code can't do that because everyone else also has Claude Code. Alpha will still reside with brilliant, idiosyncratic human investors. Yet today, investors spend most of their time sorting through news, gathering facts, updating models, and squinting at the portfolio. We're not the first to notice that LLMs should tear through work like this, freeing up investors to express their alpha full-time. But how, exactly? What's the form factor?
WHAT WE'VE BUILT
Until now, investors have been presented with two bad options. Vertical AI-for-finance tools are stunted—they could be trapped in a webapp, restricted to certain data, built for narrow use-cases, or weighted down by cost-saving model choices on the backend. On the other end, coding agents are powerful but generic. Getting them to think like an investor (let alone like an investor at your firm), connecting them (reliably, with low latency) to all your firm's important data (both tabular and unstructured, internal and external).... it's hard!
Multiplier carries your firm that long last mile. We've centered our platform on coding agents, so it benefits as AI progresses. We ship infrastructure around those agents for customization, privacy, connectivity, self-improvement, firm-level governance, agent orchestration, and investment common sense. Clients spend most of their day in the application.
According to Scott Hobart, CIO of Mercator Partners, "we used to spend 80% of our time gathering information and 20% acting on it. Multiplier has flipped those percentages." Mercator incubated Multiplier; Hobart even came up with the name.
WHERE TO NEXT
Here are a few of our priorities:
- Rapid onboarding.Our brand promise will always be "We completely handle AI, so you can focus on investing." This irreducibly requires some forward deployed engineering, but we're automating the biggest headache—getting all data connected and getting the AI up to speed on how you invest. This makes our platform transformative on the first day, instead of the first month.
- The world's best triaging of facts.Plenty of companies make products that give investors more facts. Multiplier helps them find the right facts. But there's so much further to go. What matters to you and your portfolio? When does it matter? Where? How? Why? These questions need sharp, proactive, truthful answers.
- Replacing Bloomberg (for equity research).We're coming for the interaction layer first—long overdue!—and then subbing out data on the backend. There's no hifalutin philosophy behind this—we just want to save our clients $30k per seat per year.
You may notice the omission of "expand to other verticals." That's deliberate. We're laser-focused on making the world's best tool for discretionary public-market investors. Others can watch and apply our philosophy elsewhere, but we're moving from San Francisco to Midtown East so we can spend more time with our current and future customers. Reach out and say hi.