Market Prism is a forensic narrative engine. It exists because retail traders kept finding out — too late — that the story they were sold had nothing to do with the filing it was supposedly about.
I built Market Prism for a specific audience: the people who watched their tickers get pumped and dumped, who saw the same talking points metastasize across a hundred low-effort sites in 48 hours, and who eventually realized that "sentiment" was being manufactured upstream of the price.
A lot of this work was, frankly, fueled by rage at how blatant the manipulation has become — and a stubborn belief that retail should have access to the same kind of forensic infrastructure the buy side takes for granted. So thank you, WSB. You were the proof of concept.
Market Prism isn't an LLM wrapper. It's a seven-step pipeline that anchors every narrative claim to an actual SEC filing, scores the source authority, models how the story decays, and flags when multiple outlets coordinate around the same talking points. The language model is one tool inside it — not the product.
For most of the last decade, sentiment analysis meant counting bullish vs. bearish keywords. That game is over. AI can generate a million perfectly polished bullish tweets in a single afternoon, and the internet has crossed into structural saturation — vibe-coded blogs, SEO-pumped "analysis" sites, and content farms all racing to repeat whatever talking point was profitable yesterday.
Market Prism treats that noise as a roadmap, not a problem to suppress. Every market move starts as a story whispered in a niche corner. It moves to the mainstream. Then it reaches the saturation point — when every low-quality site on the first page of Google is repeating the same line. That moment of saturation is almost always the moment the price action reverses.
We call it narrative exhaustion, and identifying it is the entire game. Market Prism turns the dead internet into a contrarian indicator.
Three things separate Market Prism from the standard "sentiment dashboard" stack:
The whole stack is patent-pending (three applications filed). The patents matter; the goal does not depend on them. The goal is to give one person at a kitchen table the kind of forensic read that, ten years ago, only an institutional research desk could afford.
Every quant desk on Earth is staring at the same OHLC bars, the same options flow, the same Bloomberg headline tape, the same Reddit sentiment scrape. When ten thousand bots are looking at the same input, the alpha goes to zero — by definition. It's the central problem of modern markets: the data is the same, so the trades are the same, so the edge isn't there.
Market Prism is built from a different substrate entirely. The inputs are narrative-physics features — claim-level extractions, source-authority weights, coordination windows, decay curves — computed from a corpus that no off-the-shelf data vendor sells. You cannot buy this signal anywhere else, because it doesn't exist anywhere else.
That's the whole point. We are deliberately the anti-system system: not another wrapper around the data feeds the algos already chew through, but a forensic layer that runs orthogonal to them.
Under the hood, Market Prism is a machine-learning system trained on the historical relationship between narrative state and price outcome. It learns, ticker by ticker, what kind of story precedes what kind of move — and the projections it surfaces (1D, 5D, 30D, 90D move bands) are model output, not heuristic rules.
Inside the engine, every ticker is assigned its own narrative fuel rate — a physics-style coefficient that controls how fast the story burns through attention. AAPL doesn't process narrative the same way a $200M biotech does. Megacaps have huge tanks and slow combustion; small caps are dry kindling. The fuel rate is what lets the model say "this story has six trading days of runway left" instead of "sentiment is bullish."
Combine the two and you get something the rest of the stack literally cannot replicate: a per-ticker, ML-driven, physics-anchored projection of where the narrative is headed and how long it has before it runs out of fuel.
"What I genuinely love about Market Prism and its narrative engine is that it doesn't try to fix the noise; it uses the noise as a roadmap. It represents a fundamental shift from What is being said? to Why is this being said now, and who is actually behind it?"
"Market Prism treats the internet like a forensic crime scene. It looks for the fingerprints of human conviction. It recognizes that a messy, typo-filled post from a verified enthusiast carries more narrative weight than a thousand perfectly polished, vibe-coded articles that were clearly prompted into existence."
"The most profound feature is its ability to map narrative exhaustion. It identifies the exact moment a story has no more room to grow — which is almost always the moment the price action reverses. It turns the 'dead internet' into a contrarian indicator."
"In the future, we won't be looking for more information; we will be looking for better filters. Market Prism isn't just a financial tool — it's one of the first true information filters of the 21st century."
We're not promising to find the truth in the news. The post-truth digital era is a fact, not a problem we're going to solve. What Market Prism promises is to find the momentum in the story — and to show its work, all the way down to the SEC filing the narrative is allegedly tracking.
In a market increasingly designed to confuse retail, the antidote isn't more data. It's a better filter. That's what we're building.