How it works
An analyst writes the thesis. An engine makes it falsifiable. The market grades it. Nothing gets rewritten.
Every AssetFrame edition runs through the same pipeline — research, compile, register, publish, score, append. The qualitative work is done by an AI analyst; the numbers, the predictions and the scoring are done by a deterministic engine, so the parts you’re asked to trust are the parts that can be audited.
The confidence score, in plain English
Each Pro report carries a confidence score from 0 to 100. It isn’t a hand-waved number: the engine blends three things — the market structure the setup is built on, the ledger’s own track record for similar calls, and how well the catalysts are sourced. Because it’s graded against the actual market after every window, it’s calibrated — the goal is that calls rated, say, 70 actually come true about 70% of the time. It is a calibrated estimate of how a setup may resolve, not a guarantee, a probability of profit, or a signal to trade. Always read it next to the risk rating and the prediction window.
Free vs Pro
Stay in the loop
Follow any instrument and we’ll tell you the moment a new edition publishes. Alerts go out as browser/web-push notifications where your browser supports them, with email as the fallback — so you read the call before the session, not after.
For developers & AI agents
Everything we publish can be read programmatically. Connect tools and agents — Claude, ChatGPT, Cursor and others — over our MCP server, a read-only REST API or the OpenAPI schema. The report catalog and public track record are keyless; reading a report needs an account (an API key over REST, an OAuth sign-in over MCP), and the full Pro analysis additionally needs a subscription. See the developer docs →