Diesel discount platform connecting truckers to nationwide fuel networks
Mudflap operates a mobile-first fuel marketplace for independent and fleet truckers, built on Ruby on Rails and Go with native iOS/Android apps. The stack reflects a consumer-app maturity (Figma, CircleCI, Prometheus/Grafana) paired with transactional infrastructure (Salesforce, HubSpot, ADP), signaling a company scaling from product-market fit into operational complexity. Hiring velocity is accelerating across product and sales—front-end growth signals—while pain points cluster around onboarding friction, complex partner economics, and foundational data infrastructure gaps.
Mudflap is a mobile fuel-discount platform that connects truckers to diesel pricing and purchasing at truck stops across the United States. Founded in 2020 and based in Palo Alto, the company operates as a marketplace intermediary, managing relationships with both owner-operators and fleet customers on one side and a network of fuel suppliers on the other. Active projects reveal a company maturing its operational layer: mobile/web platform unification, AI-assisted onboarding flows, and design system consolidation—alongside strategic focus on reducing partner friction and scaling playbooks as account complexity increases. The data infrastructure (Snowflake, BigQuery, Databricks, Redshift) underpins pricing, fraud detection, and customer journey optimization.
Backend: Ruby on Rails, Python, Go. Frontend: iOS, Android, Figma. Data: Snowflake, BigQuery, Databricks, Redshift, Tableau. Infrastructure: AWS, Terraform, ECS, CloudFlare. Observability: Prometheus, Grafana, CloudWatch. CRM/Finance: Salesforce, HubSpot, ADP, Carta.
AI-assisted onboarding for fleet activation, mobile and web platform feature parity, design system evolution, partner experience optimization, and foundational data platform development. Projects emphasize scaling operations and removing friction from high-value account workflows.
Mudflap'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.