Process Intelligence for Semiconductor Fabs

Predict defects before they cost you millions

YieldPilot monitors your fab's process data in real-time and uses AI to catch yield-killing anomalies before they reach the wafer. No new equipment. Just smarter data.

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$50M+
Avg. annual yield loss per fab
92%
Defects are predictable with data
10x
Cheaper than hardware-locked tools

What your process data has been trying to tell you

Most fabs sit on terabytes of sensor data. YieldPilot turns it into yield.

Predictive Defect Detection

ML models trained on your process history identify drift patterns and flag anomalies before wafers reach inspection, cutting scrap rates by catching problems at the source.

Process Parameter Optimization

AI continuously analyzes the relationship between deposition, etch, and litho parameters and final yield, recommending optimal settings for every recipe and chamber.

Real-Time Sensor Monitoring

Connect your existing OPC, SECS/GEM, or CSV data feeds. YieldPilot ingests process, metrology, and equipment data without requiring new hardware installation.

Yield Impact Dashboard

Track yield trends, root cause analysis, and projected savings in one place. Every insight ties back to dollars saved, not just statistical noise.

Three steps to predictive yield

01

Connect your data

Upload historical process logs, sensor feeds, or connect directly to your MES/FDC system. CSV, API, or real-time streaming.

02

AI learns your process

YieldPilot trains on your specific recipes, chambers, and yield history. No generic models. Your fab, your physics, your predictions.

03

Catch defects before they happen

Get real-time alerts when process drift is detected. See exactly which parameter is drifting and what to adjust. Track yield improvement over time.

The $12B process control market is stuck in hardware. We're building the software layer.

Every percentage point of yield improvement is worth millions. YieldPilot makes that accessible to every fab, not just the ones that can afford $10M inspection systems.