A Foundational Model for Crypto Data
AI infrastructure and models for building intelligent, autonomous financial applications.
Value Proposition
Existing foundational models lack a disciplined understanding of blockchain primitives and the crypto ecosystem, they are trained on general data and are prone to hallucinations.
RPS AI is built from the ground up on web3 data, utilizing novel methods to significantly improve accuracy & reasoning for crypto applications.
To improve our niche AI models, we deploy smart applications in real user environments. This approach allows us to gather better data for validation and further refinement of our models.
Our Methodology
RPS AI goes beyond superficial prompt engineering of GPT wrappers. Our foundational model is trained with blockchain data and crypto context at a base level, achieving higher accuracy, reliability, and performance, capable of powering businesses at scale.
To test our models in real world environments and solving real world problems, we’ve developed smart applications that incorporate our models and launched them with businesses and users. The hard to reach data collected by these applications enrich our models and improve their performance.
Use Cases
Save on USD-EUR exchanges
Helps businesses exchange fiat USD-EUR using crypto and AI rails at 10x lower fees than banks, transparently and in minutes instead of days.
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Actively Manage Liquidity On-Chain
An AI-enabled application that helps users manage active liquidity on DEXs, optimize portfolios, and minimize impermanent loss in real time.
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Smart AI Defi Vaults
Utilizes ML to enable riskless and superior yields for stablecoin pairs, integrates with defi platforms.
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RPS Network
RPS’ AI network coordinates researchers, data curators, processors for RLHF to continuously improve the model over time.
Our Mission
AI will learn and interact with finance through the blockchain. At RPS, we’re building infrastructure for the future of fintech, powered by a purpose built crypto foundational model.
We're a team of crypto natives from Stanford and Georgia Tech with 10 years of experience in deep learning and crypto with experience productionizing LLMs since 2019.
Richard W.
CEO
Aleksa M.
CTO
Aleksandar S.
CPOBacked by real builders:
