Zigoraat provides an intelligence layer that aggregates semiconductor manufacturing data, process knowledge, and engineering expertise to give fab teams full decision context at the moment of action. By unifying tool logs, recipe histories, metrology, and inspection results, the platform eliminates manual data stitching, speeds up investigations, and enables reusable engineering knowledge across teams, helping reduce yield loss and accelerate root‑cause analysis.
Funding
Funding not disclosed
Founders
Product
Problem
Semiconductor fabs make critical engineering decisions while data about tool logs, recipes, metrology, and inspection results are stored in separate, non‑integrated systems. Assembling this fragmented information manually delays root‑cause analysis, leading to yield loss before corrective actions can be taken.
Solution
Zigoraat provides an intelligence layer that aggregates all manufacturing data sources—tool logs, recipe histories, metrology outputs, and inspection results—into a unified context for each decision point. The platform links this data with documented process knowledge and engineering expertise, enabling teams to start investigations with a complete picture rather than piecing together fragments. By presenting full process history and reusable knowledge, Zigoraat accelerates root‑cause identification, reduces yield loss, and supports more consistent process control across the fab.
Target Audience
Primary customers are semiconductor fab engineering teams, including process engineers, yield analysts, and equipment reliability groups responsible for root‑cause analysis and process control.
Features
- Centralized data lake that ingests and normalizes tool logs, recipe records, metrology, and inspection data from disparate fab systems
- Contextual view linking raw data with documented engineering knowledge and expert annotations
- Searchable process history that surfaces relevant past investigations and outcomes for reuse
- Automated correlation engine that highlights anomalies and potential root causes across data domains
- Dashboard and query interface that provides real‑time visibility into yield drivers and process drift
- Integration hooks for existing fab IT infrastructure, enabling seamless data flow without replacing legacy tools