R&D labs
Precision measurement work where raw readings need context before they can support design, validation, or applied research decisions.
Mixellume Microelectronics
Metrology-grade hardware. Embedded measurement intelligence. Semiconductor depth.
The instrument is just the starting point. Mixellume connects precision instruments, embedded measurement intelligence, and custom silicon so critical readings become trusted decisions — and instruments become the specification for the silicon beneath them.
Mixellume is aimed at environments where a measurement only becomes useful when its noise state, calibration context, drift visibility, uncertainty, and diagnostic trail can travel with it.
Precision measurement work where raw readings need context before they can support design, validation, or applied research decisions.
Instrument and reference workflows where confidence depends on calibration chain visibility, drift behavior, and defensible uncertainty.
Automated environments where SCPI-ready control, diagnostics, and measurement state help data survive repeated process workflows.
Characterization and validation contexts where deeper control of the signal chain can strengthen measurement architecture over time.
Measurement workflows are producing more data than confidence. The opportunity is not only faster instruments, but calibrated hardware that can preserve context, uncertainty, and diagnostic meaning as data moves into automated and production environments.
Before large customer fleets, deep-tech buyers look for engineering depth, execution history, and technical range. Mixellume's team covers the full stack: from metrology instruments and calibration continuity to custom ASIC design, analog front-end engineering, and silicon validation — across 22–350 nm process nodes and DC to 50 GHz.
This is the engineering base behind Series 65 — a metrology platform built with instrument discipline and semiconductor depth.
Modern R&D, calibration, production, and semiconductor workflows need data that is filtered, contextualized, traceable, and ready for decisions. The leap is not only more hardware. It is more intelligence inside the measurement chain.
The next precision instrument should not simply report a number. It should defend the number.
Series 65 connects measurement instruments, power and stimulus, calibration, reference lab systems, and a future DAQ layer into one traceable ecosystem. The platform is built on a semiconductor engineering core that makes each layer more precise than off-the-shelf components allow.
The first instrument in the platform. Pre-production precision instrument establishing the measurement architecture, firmware, SCPI automation, calibration workflow, and validation base for all platform layers above.
Customer discovery & applied research collaboration open. Pre-production platform — architecture and firmware complete.
Download Preliminary DatasheetMixellume amplifies calibrated hardware with embedded signal intelligence — filtering, compensation, drift visibility, uncertainty modeling, and diagnostics. Where needed, that intelligence runs directly in custom silicon, at measurement speed.
Filtering can suppress noise without erasing signal dynamics. Compensation can correct nonlinearity, thermal drift, and range effects. Uncertainty modeling can make measurement context portable. Diagnostics can find anomalies before tolerance is lost.
Suppress unwanted noise while preserving the useful dynamics of the measurement.
The instrument team defines the measurement problem. Semiconductor and mixed-signal capability moves more intelligence and control deeper into the architecture.
DAQ should not be positioned as a channel-count race. The opportunity is data confidence: calibration continuity, traceability, context, and measurement intelligence moving into real workflows.
R&D and calibration workflows anchored in instrument-grade confidence.
SCPI and software integration for laboratory and production test environments.
Production and cleanroom environments where raw data alone is not enough.
Context, confidence, traceability, diagnostics, and decision-ready process data.
Start with the chain
For customer discovery, applied research, production path, or strategic platform discussion.