From fragmented data to continuous insights
Turning fab, test, and quality data into actionable intelligence for faster decision-making and sustained yield improvements through automated analysis and monitoring.
The NPI → Mass Production Challenge
From first silicon through volume production, teams fight long learning loops, fragmented data, and slow cross-functional closure. The biggest drag isn't a lack of data—it's the manual work required to connect signals, drive triage, and close corrective actions across test, yield, reliability, and suppliers.
Challenge:
Bring-up and early NPI generate floods of logs, test results, and lab notes—yet triage and hypothesis testing remain manual, slowing time-table.
Where agentic AI helps:
auto-ingest lab + test logs, cluster failures, correlate with config/firmware/lot, propose experiments, track results, and maintain a living 'known-issue' database
Challenge:
Wafer sort, final test, SLT, param, yield dashboards, and defect data live in different tools and formats-correlation is brittle and people spend cycles wrangling data instead of fixing issues.
Where agentic AI helps:
build/maintain data pipelines, normalize schemas, auto-join by wafer/lot/serial/handler conditions, and generate 'golden views' for common queries
Challenge:
By the time an excursion is recognized, and scoped, bad material may already have flowed—containment depends on fast pattern recognition-and cross-lot comparison.
Where agentic AI helps:
detect anomalies, isolate affected populations, separate process vs test effects, track actions/owners, enforce rel- notification, auto-gen reports, close loops
Challenge:
The hard part isn't finding a symptom —it's driving a closed loop across FA, reliability, foundry/OSAT, test program changes, and release gates.
Where agentic AI helps:
automate FA/RMA intake, summarize evidence, draft 8D/CAPA artifacts, track actions/owners, enforce release gates, and prevent recurrence with reusable playbooks.
Value & Features
Contextualize to your organization
Institutional Knowledge Capture
Standardize best-in-class analysis methods and encode expert knowledge into repeatable workflows, ensuring consistency, accelerating onboarding, and preserving organizational know-how.
Seamless Enterprise Integration
Integrates with existing data platforms and ecosystems, including OptimalPlus (NI / Emerson), to maximize value from your current infrastructure.
Continuous learning
Learns and improves over time. Transparent reasoning for traceability.
Accelerate Yield and RCA
Multi-Dimensional Insights
Uncover yield optimization opportunities, process issues, and test efficiency gains through automated correlation across design, manufacturing, test, and reliability data
Interactive reporting and dashboards
Interactive reports which can be exported to PowerPoint, PDF, Word, Excel, etc. Reports can also be pre-built via workflows to included common analyses like RCA
AI Assistant Built for Semiconductors
Ask questions in natural language and receive instant, domain-aware analysis and visualizations—without manually stitching together data from multiple tools
Scale Intelligence
Autonomous 24/7 Monitoring
AI agents continuously monitor all products, fabs, and partners to detect yield excursions and anomalies, automatically surfacing the most critical issues for engineer review
Full Lifecycle & Portfolio Coverage
Monitor hundreds of products across every stage from wafer acceptance and sort through final test and customer returns eliminating blind spots across manufacturing and quality operations
Automatic alerts
Configurable alerts for specific yield thresholds
Core workflows
Yield excursion detection
Detect yield excursions in real-time, identify impacted lots and wafers, and assign severity automatically.
Anomaly detection
Continuous monitoring for process and test anomalies with automated classification.
Correlation & RCA
Multi-variable correlation analysis to identify root causes of failures and yield loss.
Reporting & alerts
Automated dashboards, reports, and alerts delivered to the right teams at the right time.
Yield Analysis Workflow and Impact
Current workflow (manual)
(OSAT,
Foundry)
excursion
platform
analysis
AI workflow
(OSAT,
Foundry)
agentic platform
reports
Impact
Manual workflow: Repetitive, laborious process requiring constant human intervention at every stage, taking days to weeks for comprehensive analysis with high risk of errors and missed patterns.
AI workflow: Automated end-to-end analysis with SME oversight only at decision points, reducing time from days to hours while improving consistency and coverage.
Get in Touch
Ready to accelerate your semiconductor lifecycle? Let's talk.