I'm building PhotonicOps, an offline, air-gapped telemetry ingestion and agentic hardware-triage engine for silicon photonic biosensors. That's the kind of microfluidic optical sensor used in clinical biomarker detection. It ingests resonance wavelength shift data (Δλ, picometers) at 10,000 samples/sec, cleans and analyzes it with DSP, and (in the next phase) will use a local LLM to decide on hardware remediation. Zero cloud API calls anywhere in the stack. That last constraint isn't a preference; the target environment is HIPAA-sensitive clinical infrastructure, so "call OpenAI" was never on the table.
Most technology-choice write-ups read like marketing copy for the winner. This one is about the option that lost, and why. That reasoning is what actually transfers to your next decision, not the choice itself.
The problem
The Go ingestion engine receives sensor frames over gRPC at 10kHz and needs to hand them off to a Python process for DSP: Kalman filtering, baseline subtraction, spike/anomaly detection. Both processes run on the same host. This is an edge deployment, one Apple Silicon box per clinical site, not a distributed cloud service. The question was narrow: what's the transport for that one internal hop?
