Proof is a new institutional equities execution platform.

Launching in 2020

Our Story

Finance is a bloated industry. It is opaque and old-fashioned, and it has not substantially improved through the technological revolution in the way other industries have, in part because there are tremendous barriers to entry for new innovative players.

Proof is taking a crack at changing finance for the better by starting with what we know: U.S. institutional equities trading. We are building a nimble, transparent, highly effective equities execution platform and hope to go live in 2020.

The U.S. stock market, like many other areas with finance, is chock full of conflicts of interest. The players are powerful, protectionist, and profit-driven, and they collect huge amounts of money year after year. Our previous company, IEX, has done a wonderful job exposing many of the worst aspects of the stock market and offering an alternative model for a stock exchange: one that is fair and transparent. Our hope is to continue fighting the good fight, this time by focusing more specifically on questionable practices at the broker-dealer layer of the system, and again developing a better, fairer approach.

And we don't plan to stop there. U.S. equity trading is our foothold, but we aspire to shine a light on other issues in the industry as well. Proof is not about introducing revolutionary changes that will make the existing finance system obsolete in one fell swoop; we are simply trying to tackle specific problems one-by-one from the inside.


We created various tools and documents to help us better understand and assess the market. We hope you will find them useful as well.

Find My Fills

A single stock exploration tool that can drill down into ticks for a given symbol and match your executions to trades on the tape.

Market Structure Primer

An overview of US equity trading landscape to help new hires who aren't as well versed in market structure.

Market Data Fee Calculator

A quick way of determining and visualizing the differences in cost between different patterns of market data consumption.

Medium Blog

A resource for ideas, updates, and what we're working on.


Research on various topics related to our work.


A framework for historical simulation of trading behavior.

The Team

Allison is a leading expert in cryptography and distributed computing. Prior to co-founding Proof, she was an Assistant Professor in Computer Science at Columbia University, specializing in design of cryptographic systems. Additionally, she spent the last three years as a Quantitative Researcher at IEX, where she oversaw model development. Her other past employers include the Department of Defense and Microsoft Research.

Allison earned a bachelor's degree in Mathematics from Princeton, a master's degree in Mathematics from the University of Cambridge, and a PhD in Computer Science from the University of Texas at Austin. She was named a Marshall Scholar in 2006, was featured as a Forbes 30 Under 30 in Science in 2014, and won an NSF Career Award in 2016.

Beau Tateyama
Beau Tateyama

Chief Software Architect

Beau has worked on electronic trading technology for over 15 years. Prior to joining Proof, he spent 6 years as a core contributor on the IEX technology team, helping to build out the ATS, Exchange, Listings, and Cloud systems. Before that, Beau worked at RBC on the Program Trading and Algorithmic Trading teams, eventually becoming Global Head of Algorithmic Trading Technology.

He earned a bachelor's degree from MIT where he double majored in Mechanical Engineering and Electrical Engineering & Computer Science.

Daniel was previously a co-founder and the Head of Quantitative Strategy at IEX, where he spent the past 7 years. Prior to that, he was on the U.S. equity algorithmic trading team at RBC for 3 years. In both of these roles, Daniel played a key role in the idea origination and development behind several flagship trading products including IEX's Discretionary Peg, Signal and Router, as well as RBC's THOR and Eclipse.

Daniel has a bachelor's degree in Mathematical and Computational Science from Stanford, and he was named to Forbes 30 Under 30 list in Finance in 2015. He was featured in Michael Lewis's 2014 book Flash Boys.

Han Dong
Han Dong

User Experience

Han comes from an Architecture background. Previous to Proof, he spent 3 and a half years at IEX building web applications and designing storytelling tools for its technology and products across various mediums.

He holds an undergraduate degree from the University of Waterloo and a master’s degree from Princeton, where he received the Suzanne Kolarik Underwood Prize in his graduating year.

Before Proof, Prerak spent 6 years leading the software engineering team at IEX, where he helped design and implement nearly every aspect of the core technology system. Prior to that, Prerak was a Managing Director in the Global Equities Technology group at RBC, where he oversaw the development and scale-out of the electronic trading platform globally.

Over his career, Prerak has led the build-out of multiple trading, analytics, and risk management systems serving a range of equities businesses, including Program Trading, ETF Market Making, and Electronic Trading. Prerak holds a bachelor's degree in Chemical Engineering and a master's degree in Computer Science from the University at Buffalo.


We are tracking our progress toward our launch by two dimensions: the team's current collective knowledge base and the amount of tangible work completed. In the spirit of full transparency, you can find a summary below of where we believe we stand and where we're currently focusing. We will also post regular updates to our blog


Progress: 75%

Team Capability

Next Steps

  • client gateways
  • implement UX system
  • market data service
  • order management system
  • algorithmic trading engine
  • production environment
  • regulatory / supervisory reporting

Progress: 75%

Team Capability

Next Steps

  • progress through FINRA approval process
  • obtain all necessary approvals

Progress: 60%

Team Capability

Next Steps

  • identify key execution quality metrics
  • design key features
  • design day-one algo offering
  • release pre-trade analysis tool

Progress: 75%

Team Capability

Next Steps

  • consult with network
  • perform buy-side trade analysis
  • onboard day one customers

Progress: 75%

Team Capability

Next Steps

  • select DMA provider
  • engage EMS providers