See how institutional desks misread you before you file
Instead of one score, LyraMind spins up a panel of institutional analyst archetypes and reads your draft the way a room would. It surfaces where they converge, where a specific desk gets confused, and the questions each will ask.
The problem
Different desks read the same disclosure through different lenses: a macro allocator weights guidance and hedging, a multi-strategy quant wants extractable structure, a credit analyst hunts leverage and downside language. A draft that reads fine on average can still be badly misread by the one desk whose lens your weakest language happens to hit, and you find out only after you file.
How LyraMind does it
Paste the draft. The Institutional AI Simulator runs six synthetic archetypes (macro/sovereign allocator, multi-strategy quant, sector active manager, credit/risk analyst, retail reader, regulatory reader), each parsing the text through the legibility factors it weights. It computes consensus comprehension, panel agreement, and the deviations: the desks that understand the text materially worse than the room, which are your real blind spots.
What you get
A room's-eye view of your draft: consensus comprehension, panel agreement, the specific desks that read it worst with the factors that tripped them, and the ranked questions the filing will trigger. Fix the blind spots before the real desks hit them. The demo simulates on any text you paste, so your own draft works the same way.
- Paste the draft disclosure
- Six synthetic desk archetypes each read through their own lens
- Consensus comprehension and panel agreement
- Deviations: the desks that read it worst, and why
- Predicted questions ranked by how many desks ask them
- Live frontier models can join the panel when configured
Questions
Are these real institutions' models?
No. They are deterministic synthetic archetypes, honestly labeled, never named as a firm they are not. They represent lenses (macro, quant, credit, retail, regulatory), not any real desk's AI.
What does a deviation tell me?
It flags a desk that understands your draft materially worse than the room, along with the legibility factors that tripped it. That is the blind spot to fix before filing.
Can live models be part of the panel?
Yes, when the gateway is configured for live verification. Their spread of comprehension on the same text becomes an empirical misread signal. Offline, the panel is deterministic and honestly labeled as such.