Grounded market intelligence, as study inputs for your research
Research desks need structured, auditable reads they can fold into their own process, not a black box. LyraMind offers a composite LyraMind Score, an interpreted event Pulse, and an anonymized feed of where the market's unresolved questions cluster, all as study inputs.
The problem: raw feeds do not tell you what is misunderstood
Market data is a commodity, and so are single-model reads. What a desk lacks is a structured view of where attention and confusion are concentrating in real time, and a way to fold an interpreted read into research without inheriting an opaque score.
Event feeds tell you that something happened. They do not tell you the so-what, or where the market is currently confused before that confusion shows up as volume.
What LyraMind gives you: score, pulse, and a structural-confusion feed
The AI Investment Committee returns five debated lenses composited into a LyraMind Score, honest about its basis (a technical, flow, and behavioral committee, with fundamentals a planned data addition). Pulse scans a symbol universe for notable conditions, pairs each with news, and interprets the so-what, each event carrying the Trust Layer.
The Institutional Alpha Feed is a read over the platform's question flywheel: it aggregates, anonymized, which names are drawing clusters of queries the engine cannot cleanly resolve, a demand-side structural-confusion signal. It exposes no individual identity, because the flywheel stores none.
Honest scope: every one of these is a descriptive, educational study input over public information. None is a buy/sell call, a price prediction, or a performance claim. There are no backtested returns here, and the public demo runs on sample data (Pulse pulls live headlines only when a provider key is configured).
How you use it
Pull the LyraMind Score and committee lenses as one input among your own, monitor Pulse across your watch universe for interpreted events, and read the alpha feed and question insights to see where structural confusion is clustering.
Everything carries the Trust Layer (confidence, sources, evidence, reasoning, freshness) so you can trace any read back to what it is built from.
- LyraMind Score: five debated lenses composited, honest about its technical/flow/behavioral basis
- Pulse: interpreted, real-time event reads with a so-what layer and Trust Layer
- Institutional Alpha Feed: anonymized, aggregated structural-confusion signal
- Question insights: where unresolved queries are clustering across the platform
- Multi-model verification and committee views as additional study inputs
- Trust Layer on every response for full traceability
Questions
Does the alpha feed predict price or give trade signals?
No. It is an aggregated, anonymized signal describing where attention and unresolved questions cluster. It is a study input, never advice or a price prediction, and it exposes no individual identity.
Are there performance or backtest claims?
No. LyraMind makes no performance, return, or accuracy-of-outcome claims. Every output is educational analysis of public information carrying its own confidence and sources.
What is the LyraMind Score actually built from?
It composes market-brain, confluence, and regime engines into a technical, flow, and behavioral read. Fundamental inputs like earnings and valuation multiples are a planned data addition, and every lens states what it is derived from.