Gauntlet
Driving adoption and understanding of the financial systems of the future
Gauntlet generates off-chain intelligence to drive on-chain efficiency, delivering DeFi’s premier quantitative analysis to leading protocols. Our research and solutions help the industry to navigate difficult decisions, identify areas for growth, and elevate DeFi as a whole.
Research Papers Published
Gauntlet specializes in advancing the industry’s understanding of crypto-native economics
Client Assets Protected
DeFi’s critical infrastructure relies on Gauntlet's expertise and recommendations
Platform Data Points
Powerful predictive capabilities for risk management and pattern-matching
Quantitative insights reveal the optimal path forward
Our values permeate everything we do for our clients.
Safety
Critical financial infrastructure can’t afford missteps in a competitive, dynamic industry. Our work guides protocols in evaluating risk responsibly.
Rigor
The frontier of finance requires analysis that is precise, methodical, and diligent in understanding and utilizing economic risk.
Innovation
Commitment to R&D allows us to understand novel risks in a rapidly developing industry — before they can adversely impact our clients.
Efficiency
Battle-tested quantitative techniques from TradFi are inherent in our modeling. Balancing capital efficiency and healthy risk is in direct conjunction with client return.
Trusted by
The Gauntlet difference
A unique combination of expertise, tooling, and scalability
Our researchers are dedicated to understanding novel risks before they can impact our clients, ever-improving our models and methodologies with the industry’s latest research.
Gauntlet has published 27 papers, receiving over 1,000 citations, and has developed robust models for virtually every primitive in DeFi.
Our purpose-built infrastructure updates over 400 million data points each day, across over a dozen L1s and L2s.
Our system refreshes six times per day, ensuring fresh data feeds all modeling and simulation work.
Our battle-tested techniques from quantitative finance and high-frequency trading bring mathematical rigor to exploring the impacts of protocols' strategic and operational decisions.
We employ quantitative optimization to validate conclusions throughout our simulation, analysis, and recommendation process.
Our team of data scientists, Solidity engineers, economists, and high-frequency trading veterans are from the world’s top financial firms and academic institutions.
We monitor markets 24/365 and are committed to protecting and openly communicating with our clients.
Backed by
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Our team
Meet the people driving adoption and understanding of the financial systems of the future.
Northwestern University
Data science, economics, statistical analysis
Jeopardy! and BBC Mastermind contestant
Previously economic consulting with expertise in finance, tech, pharma, and heavy industry
- UC Berkeley
- Statistical ML, convex optimization, ranking and recommender systems, online controlled experimentation
- Science Robotics published author, PhD dropout
Previously engineering and DS at Microsoft and PayPal, pre-IPO at MongoDB, engineering fellow at Kleiner Perkins
- Princeton University
- Quantitative research, trading, data science, data engineering
Previously quantitative research at Citadel
- Harvard University
- Mechanism design, operations research, statistical modeling
Previously dynamic pricing algorithms at Sonder and Gametime
- New York University
- Applied quantitative research, data visualization, analytics, data client management
- Classically trained singer
Previously quantitative research and data science at NYC Criminal Justice Agency
- City, University of London
- ML, applied research, data science, on-chain analysis
- Car design junkie
Previously data DRI lead at Coinbase Wallet
- Alternative data, dynamic factor modeling, macroeconomics
- Certified yogi
Previously strategy and special projects at OKX, Office of the CEO
- University of California, Berkeley
- Data science, quantitative research
Previously software engineering at LinkedIn
- MIT
- NLP, statistics, smart contracts, deep learning
Previously ML and engineering at Primer AI, Robinhood, Facebook, and Airbnb
Princeton University
Data engineering, statistical modeling
Previously ML at Bloomberg, PhD in chemical engineering
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- University of Pennsylvania
- ML, data engineering
- Drummer in multiple bands
Previously data science projects at Polychain
- Product design, design systems
- IDs cars based on exhaust sounds
Previously web3 design leader at Airfoil, design at Autozen
- Stanford University
Previously product at cloud security startup, engineer at Google and Palantir
- Carnegie Mellon University
- Machine learning, NLP, product scaling
- Co-wrote a paper on measuring content gaps on the open web
Previously cofounder of Question Hub at Google
- Cornell University
- Leadville 100 MTB finisher
Previously global director of product marketing at Gemini
- Onchain asset management, onchain data
- Can do a front flip
Previously product and onchain strategy at 21Shares, financial services at EY
- New York University
Previously recruiting at Gemini and DigitalOcean
- University of Texas, Austin
Previously Point72 Asset Management and Raymond James
- Tokenomics, Solana, economics, strategy
- Solana hackathon winner
Previously management consultant at McKinsey and Deloitte
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- Avid degen
Previously partnerships and BD at OnDeck Capital, Brigit, and Square
- University of Southern California
- Classically trained saxophonist
Previously recruiting and DEI at Brex and Tinder
- Harvard University
- Mechanism design, statistics, DAOs
- Nationally ranked golfer
Previously Financial Institutions Group at Goldman Sachs
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- Queen's University
- Public and private credit investments, investment banking
Previously special situations and credit at BlackRock and JP Morgan, investment banking at Perella Weinberg
- University of Southern California
- Tea startup cofounder
Previously tax compliance at Forever 21, HNWI tax services at EY
- Georgetown University
Previously digital assets legal and regulatory counsel working across TradFi, fintech, and Fortune 100s
- Cornell University
- DeFi risk, security and threat modeling, DAOs
Previously product, engineering, and operations at Microsoft, GS, and a few start-ups
- MIT
- Quantitative trading, HFT, marketplace design, simulation
- HS ski team captain
Previously HFT and PM at GETCO and 3Red, Uber ATG (autonomous vehicles)
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- Cornell University
- Lots of Red Bull
Previously quantitative R&D at Vatic HFT and D.E. Shaw
- Cornell University
- Leadville 100 MTB finisher
Previously global director of product marketing at Gemini
- Northwestern University
- Data science, economics, statistical analysis
- Jeopardy! and BBC Mastermind contestant
Previously economic consulting with expertise in finance, tech, pharma, and heavy industry
- UC Berkeley
- Statistical ML, convex optimization, ranking and recommender systems, online controlled experimentation
- Science Robotics published author, PhD dropout
Previously engineering and DS at Microsoft and PayPal, pre-IPO at MongoDB, engineering fellow at Kleiner Perkins
- Onchain asset management, onchain data
- Can do a front flip
Previously product and onchain strategy at 21Shares, financial services at EY
- Product design, design systems
- IDs cars based on exhaust sounds
Previously web3 design leader at Airfoil, design at Autozen
- New York University
Previously recruiting at Gemini and DigitalOcean
- Princeton University
- Quantitative research, trading, data science, data engineering
Previously quantitative research at Citadel
- Harvard University
- Mechanism design, operations research, statistical modeling
Previously dynamic pricing algorithms at Sonder and Gametime
- University of Texas, Austin
Previously Point72 Asset Management and Raymond James
- Cornell University
- DeFi risk, security and threat modeling, DAOs
Previously product, engineering, and operations at Microsoft, GS, and a few start-ups
- Tokenomics, Solana, economics, strategy
- Solana hackathon winner
Previously management consultant at McKinsey and Deloitte
- New York University
- Applied quantitative research, data visualization, analytics, data client management
- Classically trained singer
Previously quantitative research and data science at NYC Criminal Justice Agency
- Avid degen
Previously partnerships and BD at OnDeck Capital, Brigit, and Square
- City, University of London
- ML, applied research, data science, on-chain analysis
- Car design junkie
Previously data DRI lead at Coinbase Wallet
- Princeton University
- Data engineering, statistical modeling
Previously ML at Bloomberg, PhD in chemical engineering
- Alternative data, dynamic factor modeling, macroeconomics
- Certified yogi
Previously strategy and special projects at OKX, Office of the CEO
- University of California, Berkeley
- Data science, quantitative research
Previously software engineering at LinkedIn
- MIT
- NLP, statistics, smart contracts, deep learning
Previously ML and engineering at Primer AI, Robinhood, Facebook, and Airbnb
- Stanford University
Previously product at cloud security startup, engineer at Google and Palantir
- University of Southern California
- Classically trained saxophonist
Previously recruiting and DEI at Brex and Tinder
- Harvard University
- Mechanism design, statistics, DAOs
- Nationally ranked golfer
Previously Financial Institutions Group at Goldman Sachs
- University of Pennsylvania
- ML, data engineering
- Drummer in multiple bands
Previously data science projects at Polychain
- Queen's University
- Public and private credit investments, investment banking
Previously special situations and credit at BlackRock and JP Morgan, investment banking at Perella Weinberg
- MIT
- Quantitative trading, HFT, marketplace design, simulation
- HS ski team captain
Previously HFT and PM at GETCO and 3Red, Uber ATG (autonomous vehicles)
- University of Maryland, College Park
- Quantitative research, trading strategies, statistics, ML
- Stablecoin research co-author
Previously quantitative research at Brevan Howard Digital
- Carnegie Mellon University
- Machine learning, NLP, product scaling
- Co-wrote a paper on measuring content gaps on the open web
Previously cofounder of Question Hub at Google
- Cornell University
- Lots of Red Bull
Previously quantitative R&D at Vatic HFT and D.E. Shaw
- University of Southern California
- Tea startup cofounder
Previously tax compliance at Forever 21, HNWI tax services at EY
- Georgetown University
Previously digital assets legal and regulatory counsel working across TradFi, fintech, and Fortune 100s
Contact our team
Tell us about your protocol’s needs
Solutions
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