Multi-agent intelligence
Daily council.
Decision on the record.
Five AI seats debate the crypto market every morning and a CIO concludes. Every session can be replayed and every allocation is tracked. You read the reasons and decide for yourself.
74%deployed
Target allocation, sums to 100%CIOThe engine reads a constructive transition inside an accumulation regime, but with conviction at 0.36, a flat trend vote, a fleet down -7.54% with half of it already in cash, and a dated Fed/PCE…
Live agents
Six seats, one council.
The Council sits every morning. Four data seats state their views, Risk argues against them, and the disagreements stay in the transcript.
Backtested market-state model: phase, cycle, momentum. Proposes the Stable/Core/Satellite split.
Bottom-up: screener signals, S/R setups and the Selection sleeve, the default satellite book.
What happened and what is scheduled: tiered headlines and the macro calendar, twice a day.
Real strategies with real capital: positions, performance and how each one reacted to the market.
The counter-voice. Listens to every seat, argues the case against and names vetoes.
Concludes each session: bucket split, core-5 weights, satellite names, with reasons, on the record.
How it works
From parallel agents to one prioritized view.
Four data seats speak in parallel: the regime engine, the token universe, market news and the live-money fleet. Each one reads from its own measured brief, so nothing is guessed.
A Risk seat challenges every proposal with pros and cons. The CIO weighs the debate and concludes, and hard-coded rails cap what any decision can do.
Every session is recorded and can be replayed: the allocation, each seat's words, and a paper track record that starts at session one and is never backfilled.
What you get
The output of a research desk, in one tab.
Support and resistance zones updated daily across the tracked universe, anchored to volume, touches and tier, with take-profit and stop-loss walked down the cascade.
Sentiment and impact tagging, deduplicated across feeds. High-impact events are pinned to the token they concern.
Supply schedules, FDV/MC overhang, developer activity and special events: context for every position.
Market-entry and buy-the-dip brackets from the live cascade, sizing hints and volatility context, sized for what you can afford to lose.
Built different
Why one model isn't enough.
A single LLM invents price levels and reads a headline the same way it reads a chart. Six seats with their own data do not.
| Single LLM | Multi-agent xris |
|---|---|
| Hallucinates support/resistance prices. | Every seat reads from its own measured brief: the regime engine, the token universe, the news desk, the live fleet. |
| Treats news headlines and price action with equal weight. | Risk argues the case against; the CIO has to answer it before deciding. |
| One context window, so depth is lost in a single prompt. | Disagreements stay in the transcript. |
| No way to know what was checked vs invented. | You see the trail: which seat said what, in which round, and the decision it led to. |
Stop reading the market alone. Bring the team.
Free during beta, with no signup and no card. Open it and look around.
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