Aerospace LLM Evaluation with Domain Expert Scoring
Combine automated checks with expert scoring, traceable tests, and release gates to evaluate aerospace LLMs and prevent unsafe deployments.
Tag
Articles tagged “AI Strategy” on Ryshe.
Combine automated checks with expert scoring, traceable tests, and release gates to evaluate aerospace LLMs and prevent unsafe deployments.
Secure Azure OpenAI traffic with HTTPS on every hop: enforce TLS, configure private endpoints and DNS, and test allowed/blocked paths.
Measure MRR@10 for Azure AI Search: define relevance, build judged queries, compare retrieval setups, and track production metrics.
Most AI governance frameworks are written for banks with compliance armies. Here's a practical AI governance framework for mid-market companies — five parts, real artifacts, and a 90-day plan to stand it up.
Match oversight to task risk—use HITL, HOTL, HIC, confidence routing, observability, and staged rollouts to prevent legal, cost, or safety failures.
Assess AI pilots in AEC and manufacturing: check data readiness, ownership, 30–90 day pilot ROI, and blockers before launch.
AI track-and-trace builds a clean, auditable genealogy across machines, MES, and ERP to speed containment and shrink recall scope.
Treat EASA alignment as an early task: define AI role and boundaries, map requirements, use runtime guards, and retain traceable evidence.
How AI scorecards spot supplier risk - focusing on data quality, explainable models, and governance for reliable action.
Standardize intake, score use cases, enforce governance, and plan delivery waves to turn Azure AI requests into funded roadmaps.
AI methods to detect and stop free-trial abuse: anomaly detection, identity clustering, behavior scoring, velocity checks, pattern matching.
Automate overnight dispatch on Azure: voice intake, AI transcription and classification, SOP retrieval, governed escalation, and audit trail.