Automate your hardware test workflows.

Reduce validation time, eliminate repetitive lab work, and run complete test matrices automatically— without hiring a full test automation team.

8+ years experience in hardware validation, power electronics, and test automation.

Lab bottlenecks that slow hardware teams down

Generating test matrices

Automatically create full test plans from requirements and specifications.

Automated parameter sweeps

Voltage, current, load, temperature, duty cycles, timing—without manual intervention.

Controlling lab instruments

PSUs, e-loads, oscilloscopes, multimeters, signal generators, chambers.

Data capture & reporting

Consistent logging, plotting, and automatic report generation.

Calibration sequences

Standardized procedures for repeatable, documented calibration routines.

Regression testing

Fast validation of new revisions against previous baselines.

What you get

Professional-grade test automation solutions tailored to your lab.

  • A repeatable automation workflow

    Standardized execution that any team member can run reliably.

  • Configurable test templates

    Adaptable frameworks for product variants, revisions, and new specs.

  • Instrument control scripts (Python)

    Maintainable interfaces for your existing lab equipment.

  • Automatic data collection

    Structured datasets ready for analysis, dashboards, or ML.

  • Certification-ready reports

    Consistent documentation for internal reviews or customer delivery.

How it works

1. Call

Review your test setup, bottlenecks, and instruments.

2. Proposal

Receive a detailed proposal with timeline and cost for your automation project.

3. Automation

Implement complete workflows with sweeps, logging, and reports.

Past automation projects

Examples of manual processes transformed into automated workflows.

Motor brake automation with Python script

Automated Brake Matrix Testing

Replaced a manual procedure where operators needed to set a matrix of speeds and brake levels, measure power, and wait for the roller to cool down. A Python script was created that made this process 100% automatic, eliminating human error and significantly reducing test time.

DC converter characterization with deep learning

DCDC Converter Characterization

A deep learning algorithm was developed to automatically identify edge cases and determine if DCDC converters are within specification. This replaced manual testing processes and improved detection accuracy for out-of-spec units.

Ready to automate your test workflows?

Book a call to review your current lab setup and identify the fastest wins for automation.