Fixed-ops platform for franchise auto dealers combining scheduling, communications, and service workflows
myKaarma operates a unified SaaS platform for automotive fixed operations, built on Java, Python, and AWS with Salesforce, Elasticsearch, and MySQL underpinning dealer workflows. The company is actively rebuilding its core platform while adopting LLM APIs and AI/ML integrations—a signal of feature expansion toward AI-driven service efficiency. Hiring is sales-led (6 roles across dealer success and account management) with engineering support (2 roles), suggesting a shift toward customer success and retention as core operational levers alongside product modernization.
myKaarma delivers a fixed-operations platform purpose-built for franchise auto dealers, consolidating scheduling, communications, payments, pickup/delivery logistics, video-based pre-sale inspections (MPI), and business development center (BDC) tools into a single interface. The product integrates deeply with dealer management systems (DMS) and third-party software via native connectors and open APIs, enabling dealers and OEMs to extend functionality. Founded in 2012 and headquartered in Long Beach, California, the company serves mid-market dealer groups and operates with a 51–200-person team split between product engineering, sales, and customer operations.
myKaarma runs on Java, Python, and C# for backend services, with iOS and Android mobile apps. Infrastructure is AWS-native (RDS, Aurora), with Elasticsearch for search, MongoDB and MySQL/MariaDB for data, Redis for caching, and Prometheus + Grafana for observability.
Core projects include platform rebuilding, LLM API development, AI/ML solution integration, and AI-enabled feature adoption. Secondary focus areas are servicecart digital MPI training, vendor relationship management, and hiring/employee engagement optimization.
myKaarma's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.