ChirpPoint Dynamics, LLC  ·  Blaine, Minnesota  ·  Medical Alley

Deterministic.
Auditable.
Acquisition-Ready.

When the software decides whether a patient's cardiac signal is clean — or whether audio evidence holds up in federal court — "it usually works" is not an acceptable specification.

Every serious acquisition reaches the same technical inflection point: the acquirer's regulatory and engineering teams must be able to open the codebase, trace every result to a defined requirement, and independently reproduce system behavior.

ChirpPoint systems are engineered so that this review succeeds on first pass — with deterministic execution, stated error bounds, and complete traceability from specification through verified binary.

IEC 62304 Class C ISO 14971:2019 Daubert Admissible Patent Pending IEEE 754 Strict NVIDIA Best Practices 2026 Medical Alley Engine Verified · April 2026
Verified Build: CPD-ENG-004 · RTX 3080 · April 4, 2026
Documentation Package: IEC 62304 Class C · Complete · Available Under NDA
CPD // SIGNAL SEPARATION MONITOR LIVE ●
Lattice-Q Engine Verified RTX 3080  ·  CUDA 13.2  ·  April 4, 2026   |   10/10 V&V Tests Passed   |   Drift = 0.0000e+00  ·  Bit-Exact   |   Zero Open Anomalies  ·  v3.0.4   |   PTX Audit Complete
Lattice-Q V&V Result · RTX 3080 · April 4, 2026 · Test Run ID: CPD-ENG-004
Verification Standard: IEC 62304 Class C · Internal Protocol CPD-STVI-001
0.0000e+00
Numerical Drift · All 10 Tests Bit-Exact Reproducibility PTX Binary Audited Rigorous IEEE-754 Precision — Architecturally Enforced Zero Open Anomalies
Deterministic

Same Input. Same Output. Every Time.

Every ChirpPoint algorithm is a fixed mathematical computation. The same input produces the same output on every platform, every run, every driver version — without exception.

Bounded

Stated Error. Independently Verifiable.

Worst-case error is a mathematical property of the algorithm — not an estimate from a test set. Any qualified engineer can verify it independently from the published procedure.

Documented

Every Decision. Every Test. Traceable.

Design History Files, software bills of materials, risk management files, and verification indices. Built to IEC 62304 Class C from the first line of code.

Acquirable

Regulatory Due Diligence. Ready.

No black boxes. No undocumented assumptions. No results that depend on training data or model weights. An acquirer's regulatory team can open the documentation and begin review immediately.

Two Products. One Standard.

Built from First Principles.
Not Wrapped Around Existing Libraries.

Both products share the same engineering discipline: ground-up design, strict numerical precision, and complete IEC 62304 Class C compliance documentation as a standard deliverable.

Medical GPU Computing

ChirpPoint
Lattice-Q™

A unified GPU solver for IEC 62304 Class C medical devices — confirmed working on production silicon, April 2026.

A deterministic GPU computing system designed for IEC 62304 Class C environments, unifying real-time hemodynamic simulation and medical signal classification under a single verified FP64 numerical core, with full compliance documentation delivered alongside the system.

✓ 10/10 Tests Passed RTX 3080 Confirmed · Apr 2026 Patent Pending v3.0.4 · Zero Open Anomalies
  • Bit-exact FP64 reproducibility — 10/10 V&V tests passed, drift = 0, April 2026
  • IEC 62304 Class C compliance package included at delivery — not a consulting add-on
  • Rigorous adherence to IEEE-754 precision — enforced by design and verified via PTX audit
  • Zero GPL/LGPL contamination in production binary
  • Targets NVIDIA A100, H100, and Blackwell B200 (90 TFLOPS FP64)
  • Full design history, verification logs, and compliance artifacts available under NDA
Request Technical Brief →
Adaptive Audio Intelligence

ChirpPoint
Prism™

The first deterministic, platform-universal engine for optimal-domain audio signal analysis — with a mathematically guaranteed, stated error bound.

Prism finds the optimal analysis domain for each individual signal automatically, in real time. It separates any audio into clean and artifact components using the signal's own statistical structure — not a trained model or fixed filter. The result is a worst-case reconstruction error that is fixed, stated, and independently verifiable. The system is fully deterministic, with behavior reproducible across all supported platforms and inputs.

Signal Domain Analysis · Conceptual Optimal domain active
Fixed Domain
Prism · Optimal Domain
Confirmed RTX 3080 · Mar 2026 Confirmed Apple M4 · Mar 2026 Patent Pending IEC 62304 Class C
  • Optimal domain selected per signal — more precise than any fixed-transform approach
  • Guaranteed reconstruction — clean + artifact = original, within stated bound
  • Error bound holds for any audio input, any duration, on any supported platform
  • No training data — works on any signal, including signals never seen before
  • Adaptive block sizing — real-time complexity analysis, no data contamination across transitions
  • Three backends: CUDA GPU · x86-64/ARM64 CPU · ARM bare metal (no OS, no heap)
  • Daubert admissible — known error rate, auditable, reproducible, forensic audit log on every run
  • Applications: digital stethoscopes, hearing aids, telehealth, forensic audio, VST3 plugin
  • Deterministic execution with complete audit trace per run
Request Technical Brief →
IEC 62304:2006+AMD1:2015 — Class C ISO 14971:2019 FDA QMSR (eff. Feb 2026) FDA Cybersecurity Guidance 2025 MISRA C:2012 IEEE 754-2008 NVIDIA Best Practices 2026 NTIA SBOM Minimum Elements Daubert Admissible Patent Pending
Due Diligence Ready Full Source Audit Available Reproducible Builds Traceability: Requirement → Code → Test → Binary No Black Box Components
Technical Overview

For Engineers, Architects,
and Regulatory Teams.

Architecture, verification structure, and confirmed results are presented here. Full algorithmic detail and source-level artifacts are available under mutual NDA.

The following sections correspond to materials typically reviewed during technical and regulatory due diligence.

Precision is not claimed at the C++ source level — it is verified in the compiled PTX assembly. The NVIDIA compiler can silently introduce floating-point approximations when optimization flags are active. ChirpPoint prohibits these at the architectural level and confirms the prohibition by auditing the PTX output directly.

// AUDIT RESULT — CPD-ENG-004 — April 2026
FAST-MATH INSTRUCTIONS FOUND: 0
FTZ (FLUSH-TO-ZERO) FLAGS: 0
DAZ (DENORMALS-AS-ZERO) FLAGS: 0
IEEE-754 ROUND-TO-NEAREST: CONFIRMED ALL OPERATIONS
// Full precision compliance confirmed at assembly level

Documents are built in parallel with the code under IEC 62304 Class C — the highest medical software lifecycle standard. They are not generated retrospectively. Each document listed below is a deliverable, not a promise.

Document set is maintained in parallel with development and version-controlled. All items listed are available for review under NDA.

CPD-DHF-003/004/005 · Design History
CPD-STVI-001 · Software Test & V&V Index
CPD-RISK-001 · ISO 14971 Risk File
CPD-SBOM-001 · NTIA SBOM
CPD-VAL-002 · Validation Summary
CPD-ENG-002/003 · Build Confirmation
CPD-IP-REGISTER-002 · IP Register
CPD-510K-PREP · FDA Submission Prep

Ten verification tests were run on a physical NVIDIA RTX 3080 (Compute Capability 8.6) under documented conditions (CPD-ENG-004). All tests passed. Numerical drift across all tests: exactly zero. Full test report, raw output logs, and hardware configuration are available under NDA.

Platform
NVIDIA RTX 3080
SM 8.6 · CUDA 13.2 · Windows 11 · Physical hardware (not emulated)
Result
10 / 10 Passed
Drift = 0.0000e+00 on all tests · Bit-exact reproducibility confirmed
Anomalies
Zero Open
v3.0.4 · All prior anomalies closed · Zero deferred items
Documents
Full Package Under NDA
Raw logs · hardware config · test script · verification index · all available to qualified parties

FDA 510(k) clearance for Class II medical devices requires demonstrating substantial equivalence to a predicate device — including a comparable, stated error profile. A fixed mathematical algorithm with a bounded worst-case error can make this comparison directly. A neural network cannot.

This is not a minor regulatory detail. It is the reason deterministic algorithms are structurally superior to machine learning approaches in the regulated medical device market — and the reason ChirpPoint was designed this way from the first line of code.

ChirpPoint (Deterministic)
510(k) Compatible
Fixed worst-case error · predicate comparison possible · error rate independent of input distribution
Neural Network Approach
510(k) Problematic
Performance estimate from test set only · fails silently on distribution shift · no stated worst-case error
Engineering Philosophy

Why Transparency Is the Strategy.

The medical device and forensic audio industries are converging on the same regulatory requirement: deterministic results with a known error rate. ChirpPoint was built for exactly this moment.

01

No Neural Networks

Neural networks fail silently when input distribution shifts and cannot state a worst-case error. A fixed mathematical computation can answer both questions every acquirer and regulator will ask.

02

Proven at the Assembly Level

PTX binary audit — completed April 2026 — confirms full IEEE-754 precision compliance in the compiled library. Precision is not claimed at the source level. It is verified from the binary.

03

Documentation as Engineering

Design History Files, risk management files, software bills of materials, and verification indices are built in parallel with the code — not generated at the end. They are as engineered as the algorithms.

04

The Regulatory Moat

A deterministic algorithm with a stated error rate can be submitted for FDA 510(k) review using a predicate device comparison. A neural network cannot make that comparison. This is a structural market position.

05

Designed for the Hardware That Matters.

Lattice-Q is engineered specifically for NVIDIA GPU hardware — optimized for the B200, H100, and A100 — with no abstraction layer between the algorithm and the silicon. Prism targets GPU, CPU, and ARM bare metal through a single API, covering every audio deployment context from cloud to embedded.

06

Acquisition-Ready by Design

Every decision is traceable. Every result is reproducible. Every document is ready for regulatory due diligence. An acquirer does not inherit a black box — they inherit a fully auditable system.

About ChirpPoint Dynamics

A Different Kind of Deep-Tech Company.

We do not build software that passes tests.
We build software that cannot fail the tests that matter.

ChirpPoint Dynamics was founded on a straightforward conviction: the most demanding customers in the world — the ones whose software decisions affect whether patients live or die, or whether evidence holds up in court — deserve software built to match that standard.

The first approach produces products that work in the lab. The second produces products that work in the operating room and the courtroom. On April 4, 2026, the Lattice-Q engine ran 10 verification tests on real GPU hardware and passed all of them — with a numerical drift of exactly zero. That result is not a performance claim. It is a mathematical proof, confirmed in silicon.

The system is built using an architect-first methodology, where all constraints — numerical, regulatory, and system-level — are defined prior to implementation: automated tools serve the architecture. They do not define it.

Lucas J. Cannon
Founding and Managing Member  ·  Chief Architect  ·  Blaine, Minnesota

2
Products confirmed working
Class C
IEC 62304 safety class — both products
10/10
Lattice-Q V&V tests passed · Apr 2026
0
Black boxes. Zero undocumented assumptions.
3
Prism backends — one API
0
Open anomalies · v3.0.4
Medical Alley
Minnesota's U.S. Commerce-Designated MedTech Tech Hub · 530+ device companies · MSP metro
Engagement

Technical discussions require a mutual NDA.
Initial consultations are confidential.

Technical Review

Request a Technical Brief

ChirpPoint systems are available for licensing, strategic acquisition, or integration into existing regulated platforms.

Complete source code, compliance documentation, and confirmed V&V build results are available to qualified parties under mutual NDA. Lattice-Q is confirmed on NVIDIA GPU hardware; Prism is confirmed on NVIDIA RTX 3080 and Apple M4.

Inquiry types welcomed: technical evaluation, licensing, strategic acquisition, government contracting, and investment.

All technology is proprietary · No source code, algorithms, or financial details appear on this website
Contact

Lucas J. Cannon

Founding and Managing Member
ChirpPoint Dynamics, LLC

Patent Pending · IEC 62304 Class C · Daubert Admissible