Sharpe

AI agents and infrastructure for quantitative trading research.

Sharpe provides AI agents and infrastructure for quantitative research and financial data science, bundling petabytes of market data together with high-performance computing infrastructure to compress the time it takes traders and quant researchers to go from an idea to a deployable, profitable strategy. Quantitative research traditionally requires significant infrastructure investment — data acquisition, storage, compute, and tooling — before a researcher can even begin testing a hypothesis; Sharpe removes that overhead by providing the data and infrastructure layer as a managed service alongside AI agents that assist with the research process itself. The platform has reported adoption among top quantitative trading firms, reflecting credibility at the most demanding and performance-sensitive end of the financial industry. It targets mid-market and enterprise financial institutions engaged in quantitative trading and differentiates through the combination of data scale, infrastructure performance, and AI-assisted research workflow in a single platform.

Compliance

SOC 2

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Key Features

Petabyte-scale market data: Provides access to extensive historical and real-time market data, removing the need for quant teams to separately source, clean, and maintain their own data infrastructure.
High-performance computing infrastructure: Offers the compute infrastructure required for backtesting and research at the speed and scale quantitative trading demands, without requiring firms to build and maintain their own infrastructure.
AI research agents: Deploys AI agents that assist with the research process — hypothesis generation, data analysis, strategy iteration — accelerating the path from idea to testable strategy.
Idea-to-deployment workflow: Designed to compress the full research cycle, from initial hypothesis through backtesting to strategy deployment, into a significantly shorter timeframe than traditional quant research infrastructure allows.
Multi-model architecture: Uses multiple underlying LLM providers to power the various research and analysis tasks within the platform.

Use Cases

For quant trading firms accelerating strategy research: A quantitative trading firm wants to test a new strategy hypothesis quickly without provisioning new data and compute infrastructure — Sharpe provides the data, compute, and AI research assistance needed to go from idea to backtested result rapidly.
For financial data science teams without large infrastructure budgets: A smaller quant team or hedge fund without the resources to build petabyte-scale data infrastructure in-house uses Sharpe to access institutional-grade data and compute as a managed service.

Pricing MODELS

Saas subscription

Pricing Summary

Sharpe uses a SaaS subscription model with custom enterprise pricing for larger organizations. Specific pricing tiers are not publicly listed — firms contact the company for a quote.