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.

This page is a controlled disclosure subset. Full system architecture, algorithmic implementation, and internal design are not disclosed here.

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-004/006 · RTX 3080 · April 8, 2026
Documentation Package: IEC 62304 Class C · Complete · Access Restricted · Qualified Parties Under Executed NDA
CPD // SIGNAL SEPARATION MONITOR LIVE ●
Lattice-Q Engine Verified RTX 3080  ·  CUDA 13.2  ·  April 8, 2026   |   10/10 V&V Tests Passed   |   Drift = 0.0000e+00  ·  Bit-Exact   |   Zero Open Anomalies  ·  v3.0.5   |   Physics Validation  ·  Pass
Lattice-Q V&V Result · RTX 3080 · April 8, 2026 · Test Run ID: CPD-ENG-006
Verification Standard: IEC 62304 Class C · Internal Protocol CPD-STVI-001
0.0000e+00
Numerical Drift · All 10 Tests Bit-Exact Reproducibility Binary-Level Precision Verified IEEE-754 Compliance Confirmed Zero Open Anomalies Physics Validation Suite — Pass
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. Verification protocol and numerical bounds are available to qualified parties under executed NDA.

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.

Defensible

Built for the Courtroom and the OR.

Daubert admissibility requires a known error rate, a testable method, and a forensic record. Every Prism processing run satisfies all three by construction. Every Lattice-Q result is reproducible to the bit on the hardware it was validated on.

Moat

The Compliance Gap Is Structural.

FDA 510(k) predicate comparison requires a stated, bounded error rate. A deterministic algorithm has one by mathematical definition. A neural network does not — and cannot acquire one by retraining. This is not a feature advantage. It is an architectural one.

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™

The first commercially available, audit-ready unified GPU solver for IEC 62304 Class C medical devices — confirmed 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 Physics Validation · Pass Patent Pending v3.0.5 · Zero Open Anomalies
  • Bit-exact FP64 reproducibility — 10/10 V&V tests passed, drift = 0, April 2026
  • Physics validation suite confirms correct physical results on real, varying input — not merely reproducible output
  • Fluid simulation engine validated against a canonical peer-reviewed benchmark — RMS convergence 9.552e-07
  • Anomaly classification engine confirmed correct thermodynamic ordering across all input classes
  • IEC 62304 Class C compliance package included at delivery — not a consulting add-on
  • IEEE-754 precision compliance enforced by design and independently verified at the binary level — enforcement methodology not disclosed
  • 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 for review under mutual NDA as part of technical due diligence
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 inherent properties — 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. Algorithmic implementation is not disclosed in this document.

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 processing architecture — block-level implementation specifics not disclosed
  • Three backends: CUDA GPU · x86-64/ARM64 CPU · ARM bare metal — numerically identical output across all three
  • 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.

This section presents a limited, controlled view of architecture and verified results. Core algorithmic implementation, internal design, and numerical bounds are not present in this document.

Architecture, verification structure, and confirmed results are presented at a high level. Detailed algorithmic behavior, validation datasets, and source-level artifacts are maintained in a controlled disclosure environment and made available to qualified parties under mutual NDA as part of formal technical due diligence.

Controlled Disclosure Notice: This section is intentionally limited to architectural and verification-level visibility. Full implementation detail, numerical bounds, and system internals are accessible within the ChirpPoint technical data room under executed NDA.

The following represents a controlled subset of materials available during formal technical and regulatory due diligence. Full detail requires executed NDA.

IEEE-754 precision compliance is enforced at the binary level and independently verified against the compiled output. The specific enforcement mechanisms, compiler constraints, and audit methodology are not disclosed in this document — they are available under executed NDA as part of the technical due diligence package.

// AUDIT RESULT — CPD-ENG-004/006 — April 2026
PRECISION COMPLIANCE: CONFIRMED
APPROXIMATION ARTIFACTS: NONE DETECTED
IEEE-754 ROUND-TO-NEAREST: CONFIRMED ALL OPERATIONS
// Full audit methodology and raw results withheld · Available under NDA

The documentation set listed below exists and is maintained in a review-ready state. Each item is a confirmed deliverable. Content, structure, and version history are not disclosed in this document — access is restricted to qualified parties under executed NDA as part of formal due diligence.

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

CPD-DHF-003/004/005/006 · Design History Files
CPD-STVI-001 · Software Tool Validation Index
CPD-RISK-001 · ISO 14971 Risk Management File
CPD-SBOM-002 · SBOM v2 · NTIA Format
CPD-IP-REGISTER-002 · IP Register
CPD-THREAT-001 · STRIDE Threat Model Report
CPD-UEF-001 · Usability Engineering File · IEC 62366
CPD-EU-001 · EU MDR Annex II Mapping
CPD-PMS-001 · Post Market Surveillance Plan
CPD-TRL-001 · Technology Readiness Level Schedule
CPD-API-001 · Doxygen API Documentation · Full Codebase
CPD-BUILD-001 · Build, Install & Test Guide v3
CPD-510K-PREP · FDA 510(k) Submission Prep

Ten verification tests were run on a physical NVIDIA RTX 3080 (Compute Capability 8.6) under documented conditions (CPD-ENG-006). All tests passed. Numerical drift across all tests: exactly zero. Full test report, raw output logs, and hardware configuration are available for review under mutual NDA as part of technical due diligence.

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
v3.0.5 · SA-022 through SA-027 resolved REV 2 · Zero deferred items
Documents
Full Package Under NDA
Raw logs · hardware config · test script · verification index · all available to qualified parties

The IEC 62304 V&V suite confirms determinism and reproducibility — that the same input produces the same output. The physics validation suite confirms something distinct and additional: that the engine produces correct physical results on real, varying input. Reproducible wrong physics would pass V&V and fail physics validation. Both suites are required for medical deployment confidence.

Fluid Simulation Engine
Validation Pass
Validated against a canonical peer-reviewed fluid dynamics benchmark. RMS convergence at 150,000 steps: 9.552e-07. Correct Navier-Stokes fluid dynamics confirmed.
Anomaly Classification Engine
Validation Pass
Correct thermodynamic ordering confirmed across all input classes per published reference. Normal · Anomaly · Noise correctly ranked.
Benchmark Basis
Peer-Reviewed Literature
Both engines validated against published, citable references. Citations and full test programs available for review under mutual NDA as part of technical due diligence.
Distinction
Beyond Reproducibility
V&V confirms the engine is deterministic. Physics validation confirms the engine is correct. Both properties are required. Both are now confirmed.

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 8, 2026, the Lattice-Q engine completed its REV 2 validation — 10/10 V&V tests at exactly zero numerical drift, plus a physics validation suite confirming correct physical results against peer-reviewed benchmarks. That combination is not a performance claim. It is documented, reproducible engineering, 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 · v3.0.5
Medical Alley
Minnesota's U.S. Commerce-Designated MedTech Tech Hub · 530+ device companies · MSP metro
Controlled Disclosure

Technical Due Diligence Materials

ChirpPoint maintains a complete, audit-ready documentation and verification package. Access is provided to qualified parties under mutual NDA as part of formal technical and regulatory review.

System & Source
  • Full source code (CUDA, CPU, embedded)
  • Build system and reproducible build scripts
  • Compiler configurations and flags (audited)
  • Platform-specific implementations (no abstraction layer on Lattice-Q)
Verification & Testing
  • Complete V&V test suite and execution logs
  • Physics validation suite and benchmark comparison results
  • Hardware configuration records (GPU/CPU targets)
  • Deterministic reproducibility validation artifacts
Compliance & Documentation
  • IEC 62304 Class C Design History Files (DHF-003 through DHF-006)
  • ISO 14971 risk management file with quantified risk scores
  • IEC 62366 Usability Engineering File
  • EU MDR Annex II technical documentation mapping
  • Post Market Surveillance Plan
  • Software Bill of Materials v2 (NTIA format)
  • STRIDE Threat Model Report (FDA Cybersecurity Guidance 2025)
Traceability & Audit
  • Requirement → implementation → test trace matrix
  • PTX-level audit results and compiler verification
  • Doxygen API documentation — generated from full codebase
  • Software Tool Validation Index (STVI) — all development tools validated
  • Error bounds and numerical behavior documentation
  • Versioned build artifacts corresponding to test runs
Controlled Disclosure: Full source code, verification logs, test artifacts, and compliance documentation are maintained in a review-ready state and are made available to qualified parties under mutual NDA as part of formal due diligence.
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
Controlled Disclosure: Full source code, verification logs, test artifacts, and compliance documentation are maintained in a review-ready state and are made available to qualified parties under mutual NDA as part of formal due diligence.
Contact

Lucas J. Cannon

Founding and Managing Member
ChirpPoint Dynamics, LLC

Patent Pending · IEC 62304 Class C · Daubert Admissible