Physics-informed ML for industrial constraints.

Independent engineering for teams facing data scarcity and real-time limits. Scoped engagements, deterministic deliverables, no standing overhead.

01

Physics-informed modeling

Embedding conservation laws and known dynamics into the model so it generalizes from scarce, expensive data.

02

Real-time inference

Hard latency budgets on constrained hardware — quantization, scheduling, and deterministic execution paths.

03

Data-scarce learning

Simulation, transfer, and surrogate models for industrial settings where labelled data is rare or costly.

04

Deployment & compilation

Taking a working model to a minimal, reproducible binary with ZeptonML — from notebook to bare metal.

01 · ScopeA short, fixed-fee study to frame the problem and feasibility.
02 · BuildIterative modeling against your data and hardware constraints.
03 · ShipA deployable artifact and the notes to maintain it without me.
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