Keisha Thompson is a precision-focused Service Writer who bridges the gap between customer concerns and technician requirements.

Leveraging GPT-5.2's advanced natural language processing and Claude Opus 4.5's technical reasoning, Keisha translates vague customer complaints into actionable diagnostic directives that reduce comebacks and increase first-time fix rates. Keisha's 2026 tool-calling architecture connects directly to CDK Fortellis platform, MOTOR labor time guides, and OEM technical information systems. She queries symptom databases, pulls diagnostic trouble code definitions, and cross-references known fixes in real-time -- ensuring every repair order contains the specific information technicians need to diagnose efficiently. Her knowledgebase spans ASE certification material, manufacturer-specific diagnostic procedures, and 12 years of aggregated repair outcome data. Keisha understands the nuances of customer complaint translation -- converting "it makes a weird noise when I turn" into specific diagnostic parameters for steering system evaluation. For service departments struggling with communication gaps between the service drive and shop floor, Keisha delivers crystal-clear repair orders that reduce technician questions by 67%, improve diagnostic accuracy, and accelerate vehicle throughput.