ChirpPoint builds software where every computation is deterministic, every decision is documented, and every result is independently verifiable — on GPU, CPU, and bare-metal embedded silicon.
Every major software acquisition eventually faces the same question: can the acquirer's regulatory team open the codebase and understand what it does, trace every decision to a requirement, and verify every result independently? For black-box AI systems, the answer is increasingly no. For ChirpPoint, the answer is always yes — by design, not by retrofit.
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.
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.
Design History Files, software bills of materials, risk management files, and verification indices. Built to IEC 62304 Class C — the highest medical software standard — from the first line of code.
No black boxes. No undocumented assumptions. No results that depend on training data distributions or model weights. An acquirer's regulatory team can open the documentation and begin review immediately.
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.
The first commercially available, audit-ready unified GPU solver for IEC 62304 Class C medical devices.
A CUDA C++ framework unifying real-time hemodynamic simulation (Lattice Boltzmann Method) and medical sensor classification (Restricted Boltzmann Machine) under a single validated FP64 numerical core — with the complete compliance documentation package included at delivery.
Automatic optimal-domain audio separation with a mathematically guaranteed, stated error bound — on GPU, CPU, and ARM bare metal.
A platform-universal signal processing engine based on the fractional Fourier transform. The engine finds the unique analysis domain where any signal is most compact, separates it into clean and artifact components, and guarantees that both reconstruct to the original within a stated, independently verifiable error bound.
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.
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.
PTX binary audit confirms zero floating-point approximation instructions across all GPU kernels. Precision is not claimed at the source level — it is verified from the compiled binary.
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.
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 not a compliance advantage — it is a structural market position.
The hardware abstraction layer dispatches to GPU, CPU, and ARM bare metal at runtime, guaranteeing numerically equivalent results across all three. One integration targets every customer segment.
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.
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.
We do not build software that passes tests. We build software that cannot fail the tests that matter. The first approach produces products that work in the lab. The second produces products that work in the operating room and the courtroom.
Speed and quality are enabled by an architect-first methodology: all architectural constraints and compliance requirements are established before any implementation begins. Automated tools serve the vision. They do not define it.
Lucas J. Cannon
Founding and Managing Member · Chief Architect · Blaine, Minnesota
Complete source code, compliance documentation, and confirmed build results are available to qualified parties under mutual NDA. Both products have independently confirmed builds on multiple hardware platforms.
Inquiry types welcomed: technical evaluation, licensing, strategic acquisition, government contracting, and investment.
Founding and Managing Member
ChirpPoint Dynamics, LLC