Fractiq is an agentic Elliott Wave engine — a fintech product that puts a trader's chart to a panel of leading frontier AI models (Claude, GPT, Gemini, Grok, Qwen) rather than trusting one. Each model labels the chart independently; Fractiq cross-examines every count against Elliott's rulebook, keeps the read that survives, and returns the exact price level that would break it. Where the models agree, confidence rises; where they split on direction, it's flagged — not hidden. One AI hands you a confident count and never tells you when it's wrong — Fractiq is built to be accountable on every count.
A single AI model hands you a clean, confident wave count — and never tells you when it's wrong. Elliott Wave is subjective enough already; one model's false confidence makes it dangerous. The brief was to build a product traders could actually trust: one that holds every count to a panel of models and the rulebook, preserves dissent instead of hiding it, and is honest about the exact level that would prove it wrong.
Every mind on every count.
We shaped Fractiq from concept to live product — the positioning (an agentic Elliott Wave engine, accountable on every count), the multi-model consensus architecture that runs frontier models in parallel and cross-examines their counts against the rulebook, the octahedron synthesis engine, and the minimal, technical brand and interface that make a rigorous idea feel inevitable. A bespoke build, end to end.
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