ScalarField provides an AI‑driven Python SDK that unifies market data ingestion, compute‑intensive research, backtesting, and brokerage‑connected live trading across equities, options, crypto, prediction markets and pre‑IPO securities. The platform lets quantitative traders and fintech developers query institutional‑grade datasets, run LLM‑assisted analysis, and deploy autonomous trading agents without building custom infrastructure, while offering scalable compute, premium data feeds, and secure enterprise deployment options.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Individual traders and quantitative teams often struggle to integrate large-scale market data, compute-intensive research, and automated execution across multiple asset classes, requiring disparate tools and extensive engineering effort. This fragmentation limits the speed at which strategies can be developed, back‑tested, and deployed in live markets.
Solution
ScalarField offers an AI‑driven research and trading platform that unifies data ingestion, compute, backtesting, and brokerage‑connected execution within a single Python library. Users can query institutional‑grade datasets, run large language model (LLM)‑assisted analysis, and generate trading agents that operate continuously across equities, options, prediction markets, crypto, and pre‑IPO securities. The platform handles context‑aware prompting, compute allocation, and real‑time order routing to supported brokers, allowing strategies to move from idea to live trade without custom infrastructure. Subscription tiers provide scalable context windows, compute time, and premium data feeds, while enterprise options add private cloud deployment and custom brokerage integrations.
Target Audience
Primary customers are quantitative traders, hedge‑fund quants, and fintech developers who need end‑to‑end research, backtesting, and automated execution across multiple asset classes, as well as institutional teams requiring secure, compliant deployment.
Features
- Unified Python SDK (`scalarlib`) that provides compute, data access, backtesting, and live‑trading orchestration in a single codebase
- Access to over 200 K‑plus context window and up to 15 minutes compute per query for complex LLM‑driven research
- Institutional‑grade market data feeds including options quotes, greeks, IV, OHLCV for equities, crypto, forex, earnings calendars, insider trades, economic releases, and Polymarket prediction‑market data
- Built‑in brokerage connectors (Alpaca, Polymarket, Jupiter DEX) with support for additional APIs (Interactive Brokers, Ameritrade, Robinhood, Schwab) via bring‑your‑own integration
- Automated strategy templates marketplace and monitor/alert engine for continuous signal generation and execution
- Enterprise security features such as SSO, SAML, RBAC, SOC 2, GDPR, and HIPAA‑ready compliance, plus private VPC deployment options
- 24/7 premium support, service level agreements, and dedicated account management for high‑volume users