Built inside the financial world.
VARRD builds inside clearing firms, brokers and trading desks, on the data and workflows general LLMs never see. We strip out what is theirs and bring the rest forward: ideas tested before they trade, in financial and prediction markets, and risk seen before the loss.
The data and workflows general LLMs do not have access to.
Assets that are very hard to attain, and the years of process behind them.
Three of the assets we build on
VARRD Validation
500+ traders. 20,000 hypotheses.
Fine-tuned on their tests, with guardrails built from what they found, to help validate ideas to trade off of.
VARRD Risk
Every trader's own record.
Built from each trader's own trades, orders and positions and the clearing firm's books, and graded against what happened next. A general AI never sees them.
VARRD Validation, prediction markets
Every contract, to its outcome.
Built on years of settled prediction market history, tested with the venues' real fills and fees, so a test reads like a trade.
How we build
Built inside the moat. Offered outside it.
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01
Access
We work inside clearing firms, brokers and desks, with their data and their processes.
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02
Build
We build products on the accumulated assets behind those moats.
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03
Strip
We strip out the proprietary data. Nothing of theirs leaves.
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04
Offer
We offer what is left to the rest of the financial world.
Products
What we offer today.
Quant research · financial markets
VARRD Validation
Our quant AI. It takes ideas and turns them into quantifiable formulas, then tests them against decades of data with hard guardrails against overfitting. A strict system the AI can use but not make up, doing math it cannot hallucinate. So you can see whether an idea has an edge.
Risk management
VARRD Risk
Risk management, from reactive to proactive, with AI. One product in three versions: for the trader, the risk manager and the clearing firm. It watches every book around the clock and says what is coming before it lands, inside the AI you already use.
One product, three versions
Each version is built for that role, with its own machine learning and tools. The clearing firm can see what its risk managers and traders see, and the risk manager can see their traders, but never the other way around.
The Trader
Know what your own style and habits bring about.
Built for each trader from their own trades, orders and positions. It learns their style and habits and shows what those habits lead to, good and bad, so they become a better trader.
Example
“You are long Citibank into earnings tomorrow. The last 24 times, you lost money 22 times.”
Example
“Tomorrow is month end. In a profitable month, you typically overtrade into month end and give some back.”
The Risk Manager
A fleet working on their behalf.
Its own fleet across the whole desk, built on top of every trader's fleet, so it compounds like a flywheel. It learns the style and habits of each trader on the desk, and alerts the risk manager to potential issues before they actually happen.
Example
“Traders 1, 2 and 3 are all long gamma. The last times that happened, the book's VaR neared its limit in the days after.”
Example
“The desk has 60 positions on, but they move like one and a half.”
The Clearing Firm
No unnecessary risk taken on.
Watches every firm it clears for, so the clearing firm takes on no risk it does not need to: positions too big to get out of, crowded trades, losses above margin, clients who may not pay.
Example
“A trader at a firm you clear for holds 80% of the open interest in an out-of-the-money put expiring Friday. If nothing is done by tomorrow afternoon, they will likely be stuck, and the risk sits with you.”
Quant research · prediction markets
VARRD Validation, for prediction markets
The same quant AI, built for prediction markets. Ask about any market in plain English. It turns the idea into a strategy, refuses anything that peeks at the future, and tests it with real fills and fees. Save it, and it runs on live markets every 15 minutes, telling you when it fires.
VARRD Capital
A trading fund, from futures to prediction markets.
VARRD Capital is the fund inside VARRD. It trades on the same tools we offer: every idea tested before it trades, every position watched around the clock.
Company
The founders.
VARRD was built by derivatives traders and engineers who spent years working alongside one of the most successful futures trading firms of the past 40 years, dissecting the research process that turned raw market intuition into systematic, repeatable edges.
VARRD is that process, rebuilt from the ground up with AI. It started with research. It now covers risk and prediction markets, for the firms that run the financial world and for anyone who wants the same caliber of work.
Augie Mazza
Co-Founder
Derivatives trader and lifelong entrepreneur with deep market intuition shaped by his father, one of the top macro derivatives traders globally. Has been building with AI models since 2018. His university has him review their AI curriculum every year.
Ben Harrington
Co-Founder
Derivatives trader with an Economics degree with a focus in quantitative finance from Princeton and D1 All-American honors, bringing both analytical precision and incredible discipline to the team. Has invested countless hours refining the validation engine, ensuring its outputs meet the highest standards of statistical rigor and real-market reliability.
Henry Wedbush
Founding Member
Princeton Economics degree with D1 All-American honors, bringing both market knowledge and competitive intensity to the team. Leads the company's business and partnership efforts, aligning VARRD's development with the needs of enterprise clients.