NyquistNyquist
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Why Nyquist

The stack under financewas built for humans. The next one isn't.

Every institution runs its risk-and-research on tools nobody designed for autonomous compute. The incumbents are built for large institutions and assume humans stitch the vendor silos together. What an institutional desk gets with Nyquist: a typed bitemporal ontology spanning 42 domains, a deterministic quant core computing 34 derivative families and ALM, and autonomous research desks that debate and synthesise with explicit invalidation triggers — audit-grade, vertically integrated, and priced for the mid-market to enterprise. That gap is the opening.

★ ProblemGlue, not an operating system
★ Why nowAutonomous agents grounded in quant math
★ EdgeDeterministic quant core, not LLM wrappers
★ 01   The problem

Risk-and-research runs on tools nobody designed for AI.

  • ↗ 01
    The buy-side stack is glue. Jupyter, Excel, the terminal, Python — none designed for agents.

    An LLM bolted on top adds a seam, doesn't close one. Every new question becomes another script someone has to maintain.

  • ↗ 02
    Regulators run on hand-coded SQL. The largest supervisors build in-house.

    No vendor ships suptech with audit trails procurement accepts. Every supervisor hits the same wall.

  • ↗ 03
    Incumbents are priced for the top. Six-figure floors, six-month implementations, and a licence no fund under $500M can justify.

    Document Q&A copilots stop at the document and never run the book. Everyone else self-builds and pays the salary bill forever.

The status quo: 6 seams per investment decision
Filings → Spreadsheet → Python script → Vendor API → Chatbot → Committee memo
★ 02   Why now

Three shifts converge in 2026.

  • ★ 01
    Autonomous agent swarms can orchestrate tools. Reasoning models can now call typed mathematical APIs deterministically.

    Instead of generating speculative answers, agents call PDE solvers, yield curve builders, and VaR calculators through typed tool contracts. The model never does the arithmetic.

  • ★ 02
    Small domain models fit inside private perimeters. Compact, domain-tuned models now run on a single GPU.

    That makes in-perimeter inference realistic for a bank. Our own compact models (Pulse, Spectrum) are built for it and not yet connected: roadmap, not production.

  • ★ 03
    BCBS 239 and Basel IV demand immutable auditability. Regulators no longer accept black-box calculations.

    Every risk metric must be provably reproducible to its source tick. Nyquist embeds this in its bitemporal store: every figure carries the inputs and run that produced it.

★ 03   Start your pilot

Experience the architectural difference.

Start a 60-day paid pilot on your live book. 100% credited against your annual enterprise license.