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BASIC INFORMATION

What do you do in one sentence?

Our platform empowers traders to build AI strategies with no code to beat markets

Our solution is a no-code trading platform that democratizes algorithmic trading with an intuitive, easy-to-use interface. It's available via an affordable subscription, allowing traders to efficiently build, test, and execute AI-driven strategies.

What problem are you solving?

What do you do in detail?

The core offering of Tradery Labs is its no-code, AI-driven platform that simplifies the development, testing, and execution of trading strategies. This platform is particularly innovative due to its integration of a generalized machine learning model with cloud-based architecture, which enables rapid optimization and backtesting of trading strategies. It offers a significant reduction in the time and cost typically associated with quantitative trading, making it a potent tool for traders of all levels.

What's different/interesting about Tradery Labs?

Simulate, test, create, and deploy AI strategies faster and with greater efficiency than competitors.

Please describe your product(s)

What critical problem(s) are you solving? (In Detail)

How might your technology integrate into the existing architecture of a major financial institution?

Major financial institutions have investment and economic growth arms. We will help financial institutions serve customers with tailored builders for their investments.

What differentiates your offering from the competition? What benefit(s) does your solution aim to provide?

Our main advantage over our competitors is the way we integrate the latest advances in cloud computing with our machine learning models. This approach is highly distinctive, as it requires engineering talent that is rare to find. This is not something that could have been built 2 years ago.

We can achieve a 1000x improvement in model generation speed. This means that what would typically take days to complete can now be done in minutes, leading to faster production and a higher-quality user experience.

Our main competitors are Composer, Boosted AI, and Collective 2. We recognize the importance of continually developing a generalized machine-learning layer that can produce consistent strategies that outperform the benchmark market optimization. Our unique advantage over our competitors lies in our ability to integrate the latest advancements in cloud computing with our machine learning models. This approach requires exceptional engineering talent and could not have been developed just two years ago, as it requires rare engineering talent. It is not something that could have been built two years ago.

TEAM

How do the team/founders know each other?

Our core team met over 5 years ago, driven by a collective vision to develop cutting-edge technology that could generate resources for the benefit of individuals, focusing on Puerto Rico, home to some of our founders.

Over the years, we have successfully drawn in highly skilled and dedicated individuals who have chosen to commit their time and expertise in exchange for equity, a testament to their unwavering belief in the potential of the technology we are diligently crafting. They share our conviction in our ability to wield this technology to bring about positive change and influence the future of finance.

Our team has phenomenal talent and emotional intelligence that enables us to communicate clearly, deliberate effectively, and foster a collaborative environment to achieve remarkable outcomes.

How might your technology integrate into the existing architecture of a major financial institution?

Our technology can provide buy/sell/hold signals via a Web Service API and can automatically place trades in a customer’s electronic brokerage account.

PROGRESS How far along are you?

Our specialized machine learning model (Athena v1.4)(4yrs R&D) and deep learning model (Zeus v1.5)(3yrs R&D) strategically analyze market conditions using different techniques. This allows us to create diverse, uncorrelated trading strategies for reduced risk. These models generate real-time signals that trigger our autonomous trade bots, currently deployed on Coinbase and Interactive Brokers. Over the past four years, our bots have successfully traded $2.1m across various markets with 41 active users, achieving an aggregate average return of 65%+.

We're democratizing this technology with a new GUI for strategy building (65% complete), informed by ongoing user interviews. Our backend architecture leverages Flink and stream processing for near-instant model creation and optimization and is 75% complete.

How long have each of you been working on this? How much of that has been full-time? Please explain.

Our team has worked on this problem for four years, with members balancing full-time and part-time commitments. We've operated with a lean approach to extend our runway, focused on reaching revenue generation for sustainable growth.

What tech stack are you using, or planning to use, to build this product?

IDEA Why did you pick this idea to work on? Do you have domain expertise in this area? How do you know people need what you're making?

Our CEO Angel has 25 years of experience building and refining artificial intelligence systems and has built multiple automated trading systems. His vision for the company is loosely based on Renaissance Technologies, one of the most successful quantitative investment firms in history. He has spent the last 6 years building and testing models that trade futures contracts and underlying assets using Bitcoin, Ether, Nasdaq, and Gold. Through this work, he determined that it is possible to use data science to match and exceed Wall Street’s historical returns.

Every investor wants to achieve 25%—50% annual growth of their portfolio. We have achieved this metric twice in our history and are prepared to do it consistently, in a manner similar to how Renaissance Technology achieved a compound annual growth rate of 62% between 1988 and 2021.

How do or will you make money? How much could you make?

Our revenue model is a straightforward monthly subscription of $99 per user. We focus on a substantial market opportunity: the rapidly growing retail trading sector within the United States.

Market Opportunity Total Addressable Market (TAM): 59 million US retail traders. Serviceable Addressable Market (SAM): 11.8 million traders (we target the most active 20% of the TAM). Share of Market (SOM): We aim to capture 1% of the SAM, resulting in 118,000 traders.

Revenue Potential Monthly Revenue Potential (at SOM): $11.68 million Potential Annual Recurring Revenue (ARR) at SOM: $140.2 million This model offers significant scalability. As we refine our product and marketing, we anticipate increasing our SOM within the large, underserved market of active retail traders. This positions us for substantial revenue growth.

How do users find your product? How did you get the users you have now? If you run paid ads, what is your cost of acquisition?

Right now, people find our product in a few ways – they might discover us through Google searches, or we reach out directly on platforms like Discord, Reddit, and LinkedIn. Our early users have come from word-of-mouth recommendations and connections with our initial investors.

We're not running paid ads yet, but we have a clear plan for that. We're actively researching the best channels to reach our ideal users and will closely track metrics like cost of acquisition when we start paid advertising to ensure we're getting the most out of it.

OTHERS If you had any other ideas you considered applying with, please list them. One may be something we've been waiting for. Often, when we fund people it's to do something they list here and not in the main application.

AI-Driven Robo-Advisors for Active Trading: We're exploring the next wave in financial tech with AI-driven robo-advisors capable of active trading. These systems leverage real-time market data and advanced algorithms to dynamically adjust investment strategies, offering personalized, high-performance asset management.

Decentralized Autonomous Trading Funds on DeFi: We’ve considered creating fully decentralized trading funds that operate autonomously on DeFi platforms. Using smart contracts, these funds would execute trades and manage assets with transparency and efficiency, potentially revolutionizing asset management in the blockchain era.

Marketplace for Trading Models: Another idea is a collaborative marketplace for financial experts and AI developers to create, test, and monetize trading models. This platform would democratize access to sophisticated trading strategies, fostering innovation and providing users with new income streams."

Sovereign Wealth Generators for Nonprofits: We've thought about empowering grassroots nonprofits with sovereign wealth generators, using AI and fintech solutions to create self-sustaining income streams. This would help these organizations achieve financial independence and reduce reliance on unpredictable funding sources.

CURIOUS What convinced you to apply to Y Combinator? Did someone encourage you to apply? Have you been to any YC events?

Tradery Labs was born from a vision to revolutionize the trading landscape with an AI-powered, no-code platform. Y Combinator's dedication to fostering disruptive innovation perfectly aligns with our mission. We're particularly impressed by YC's track record of launching industry-shaping companies, like many we admire. Our confidence is further solidified by a YC alumnus advisor who experienced the program's transformative power for startups. While we haven't attended YC events yet, active engagement through webinars and forums has significantly influenced our strategy. We believe YC's mentorship, network, and groundbreaking tech culture will be instrumental in scaling Tradery Labs and empowering a new generation of traders.

How did you hear about Y Combinator?

YC is a legend in the startup community; if you're an aspiring founder, it's the first thing you find.

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