Governed agent execution
Agents operate across policies, permissions, and system boundaries, with risk controls and review gates for actions that require human approval.
Governed AI agents for enterprise data, engineering workflows, and mission-critical systems.
Emergence is an enterprise agentic infrastructure platform for deploying AI agents across complex data, engineering, and operational systems. Its agents are designed to plan, reason, and act within defined policies, permissions, and system boundaries, with controls for verification, traceability, and human review.
The platform combines semantic intelligence, persistent memory, and workflow automation. It connects structured enterprise systems with unstructured knowledge, monitors data quality, investigates issues, and can execute approved corrections. In semiconductor environments, purpose-built agents support workflows spanning design verification, new product introduction, production, yield, and sustaining operations.
Emergence is intended for organizations that need repeatable AI assisted execution in environments where decisions must remain explainable and operational actions must be governed.
Agents operate across policies, permissions, and system boundaries, with risk controls and review gates for actions that require human approval.
The platform unifies structured data with engineering knowledge such as reports, tickets, standard operating procedures, and other unstructured sources.
Long term memory retains context, validated decisions, and learned remediations so later executions can use prior institutional knowledge.
Agents assess metadata and data quality, detect drift and anomalies, generate SQL correction scripts, and support review and validation before changes are applied.
Results can include evidence links to source material such as waveforms, test logs, and prior debug sessions, supporting reproducible analysis and auditability.
Engineering teams can use agents for specification to RTL generation, simulation and formal verification support, timing closure debugging, and sign off preparation.
Teams can draft test plans, validate automated test equipment programs, and analyze NPI test data while moving from first silicon toward volume readiness.
Manufacturing and quality teams can identify excursion candidates, automate root cause analysis, assign investigations, and prioritize yield improvement experiments.
Data teams can connect fragmented sources, monitor metadata and quality continuously, investigate issues before they disrupt analytics, and apply approved data corrections.
Emergence is an enterprise platform for AI agents that plan, reason, and act across business data and systems under defined governance and verification controls.
Its semiconductor agents cover design verification, test plan generation, automated test equipment program validation, NPI test data analysis, production excursion triage, defect pareto analysis, and yield improvement.
The semiconductor solution is designed to work above existing systems. It connects EDA outputs, test systems, MES, QMS, PLM, and yield platforms rather than replacing those tools.
Yes. The platform describes human review and approval gates, including review and validation of suggested data fixes before they are applied directly to data systems.
Traffic data is for reference only.
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