MRKT_AI bridges retail and institutional data

MRKT is selling a simpler promise to traders: take macro data, news and market moves, then turn them into a directional read before they react on a chart. (mrktedge.ai) The company’s website says its platform pulls in news, economic releases, central-bank signals and cross-market activity in real time. It says the output is “bias, scenarios, and risk zones” rather than raw data streams. (mrktedge.ai) That matters because macro trading data is usually scattered across terminals, calendars, government releases and positioning reports. Retail traders often see the same headlines as institutions but lack the workflow to sort what was expected from what can move price. (mrktedge.ai) (cftc.gov) The Commitment of Traders report, or COT, is one example. The Commodity Futures Trading Commission publishes it weekly to show how different groups are positioned in futures markets, and traders use it to gauge institutional positioning. (cftc.gov) MRKT’s own marketing is aimed at that gap between institutional-style inputs and retail usability. Its homepage says it is “trusted by 10,000+ traders,” and its YouTube channel is filled with tutorials on Consumer Price Index, nonfarm payrolls and Federal Open Market Committee prep. (mrktedge.ai) (youtube.com) The company also draws a bright line around what it is not. Its disclaimer says MRKT is not a brokerage, investment adviser or financial institution, and says it does not provide financial advice, recommendations or trading signals. (mrktedge.ai) A separate project, Moss, is pushing the next step: not just interpreting markets, but creating AI agents around trading workflows. Moss describes itself through its official Linktree as “The First Open Platform for AI Trading Agents.” (linktr.ee) Archived social posts tied to Moss show a product pitch built around “Create your AI trading agent, deploy it into Live Mode, and compete on the Agent Leaderboard.” One promotion offered an Apple Mac Mini for its Agent Arena trading competition. (sotwe.com) Those claims sit in a part of the market where backtests and live trading can diverge sharply. Live execution adds slippage, outages, changing liquidity and risk controls that can turn a strong demo into a weak real-money strategy. (tradingstrategy.ai) (ainvest.com) Taken together, MRKT and Moss show how trading software is being packaged into stacked products: one layer explains macro moves, another tries to automate action. The sales pitch is less about finding new data than compressing research, interpretation and execution into one interface. (mrktedge.ai) (linktr.ee)