The Production Reality of AI Degradation
A machine learning model or LLM agent that performs brilliantly during evaluation will eventually degrade in production as customer behaviors shift, market conditions change, and API schemas evolve.
Without robust MLOps lifecycle infrastructure, enterprises discover model failure only after customers complain or compliance officers conduct an audit.
Automated Evaluation Harnesses
Logics Limited installs continuous automated evaluation harnesses directly into the inference pipeline. Every week, a representative sample of production prompts and completions is automatically evaluated against benchmark datasets for factual precision, tone alignment, toxicity, and schema compliance.
When evaluation metrics drop below predetermined enterprise thresholds, the system triggers alerts, logs the failing cases, and can automatically fall back to a more conservative model configuration.
Compliance & Governance Alignment (ISO 27001 & SOC 2)
Enterprise compliance requires answering three questions: Who accessed what data? Which model version generated this specific decision? Was sensitive proprietary information sanitized before external processing? Our MLOps governance layers maintain cryptographically verifiable audit logs that satisfy institutional compliance auditors.