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Your Agentic Trading Desk — Building the next era of agentic…
We’re building the agentic trading desk for the new operating system of markets. I used to be a trader at Tower Research and Goldman Sachs, and I’m building Scalar Field with my co-founder Ramakant, who led engineering teams at Microsoft. We’ve both spent our careers at the intersection of finance and technology, and we’re using that experience to rethink how markets are analyzed, tested, and traded in the age of agents. Scalar Field is built around a simple belief: over the next few years, agents will not just help people research markets — they will actively participate in them. They will monitor news, parse filings, track sentiment, test hypotheses, rebalance portfolios, and execute trades. They will turn ideas into strategies, and strategies into live portfolios. But today’s financial infrastructure was not built for that world. Terminals are dashboards. Backtesting tools are fragmented. Execution systems are separate. Market data is hard to unify. And most platforms still assume the human is the only decision-maker. Scalar Field changes that. We’re building an agentic trading platform where users can create financial agents that research data, backtest strategies, monitor market events, and trigger trades when specific conditions are met. The long-term vision is agentic ETFs: portfolios created, managed, and rebalanced by agents around any idea, narrative, event, or market signal. Scalar Field lets users go from thesis to backtest to live portfolio in one place. It is infrastructure for the agentic trading era.
Scalar Field offers an AI agentic trading desk that researches, decides, and executes across multiple asset classes and venues, providing 24/7 automated trading capabilities and brokerage integrations. The platform combines market research, backtesting, and execution with configurable automation strategies and a marketplace of templates and data sources.
The product operates as an AI agentic trading desk that can perform market research, backtesting, and execution across equities, options, prediction markets, and pre-IPO names. It provides: automation strategies, monitors/alerts, a strategy templates marketplace, and access to extensive data (market data, options data, earnings, insider trades, institutional flows, analyst targets, macro data, Polymarket, Jupiter DEX, etc.). It supports brokerage integrations (e.g., Interactive Brokers, Ameritrade, Robinhood, Schwab) and private cloud deployments, with different plan tiers offering varying context windows, compute time, trade fees, data feeds, and support levels. Users can try for free and scale through Pro, Enterprise, and Custom plans with private team workspaces and custom integrations.
Who it’s for: Targeted at quantitative traders, asset managers, research teams, and institutional or sophisticated individual traders seeking automated, broker-connected trading across multiple venues and asset classes.
Pricing page with multiple plan tiers and private deployments; references to coming soon integrations and enterprise customization imply ongoing product-market fit and traction signals.
Test any market hypothesis instantly — and intelligently.
Scalar Field reimagines the trading terminal to let users test market hypotheses instantly using intelligent agents. It targets traders and analysts, offering backtests, agent-driven dashboards, live reaction and trade initiation, persistent memory, and multi-hop workflows to validate ideas and generate ideas and actions.
The AI Quant: Autonomous Alpha Engine for Funds and Traders.
Superintelligent financial advisor
