AI dispatch platform and load board for owner-operator truck drivers
TruckSmarter operates a load board and AI-powered dispatch assistant for owner-operator truck drivers. The stack is AWS-native (ECS, RDS, Fargate, Redshift) with TypeScript/Node backend and React Native/Flutter mobile frontends, anchored on PostgreSQL and integrated with GPT-4. The hiring velocity is accelerating with a senior/staff-heavy engineering team (7 engineers, 6 senior+) focused on core platform architecture, ML infrastructure, and dispatch mobile experience—indicating a move toward consolidating fragmented freight logistics under a single AI-coordinated platform.
TruckSmarter provides owner-operators with a free load board and an AI assistant (Dispatch) to find and book freight more efficiently. Founded in 2021 and based in San Francisco, the company operates at the intersection of logistics infrastructure and driver-focused software. The product targets truck drivers directly—representing nearly 6% of the American workforce and responsible for 71% of US freight movement—addressing fragmentation and manual coordination that characterizes the industry. The team is actively scaling core systems architecture and deployment pipelines to support AI-powered dispatch operations across both web and mobile surfaces.
AWS infrastructure (ECS, RDS, Fargate, Redshift), TypeScript/Node.js backend, React/Next.js/React Native/Flutter frontends, PostgreSQL, GPT-4, and Terraform for infrastructure as code.
AI-powered dispatch layer, core platform and systems architecture, ML/AI infrastructure, mobile experience optimization, deployment pipelines and observability, and brand scaling for new AI products.
TruckSmarter'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.