AI-powered operational platform for construction management
Trunk Tools builds automation software for construction operations, with a founding team rooted in deep tech (SpaceX, Stanford, MIT). The tech stack reveals a dual-layer architecture: a React + TypeScript frontend with sophisticated state management (Redux, Zustand, Recoil), paired with a serious ML backbone (SageMaker, Ray, Prefect, Airflow, MLflow, Weights & Biases, Arize). The project list—multi-agent systems, knowledge graphs, document processing, and Q&A agents—reflects a company pivoting from manual workflows toward autonomous site intelligence. Hiring is senior-skewed (10 of 17 roles) and engineering-dominant, typical of early-stage AI companies scaling inference infrastructure.
Trunk Tools automates construction operations for field teams and project managers. The company targets the $13 trillion construction sector, where analog processes and document-heavy workflows remain the norm. Their product surface spans operational task automation (via multi-agent systems), intelligent document processing and Q&A, and workflow orchestration across construction-specific tools. The founding team has deployed software across 140k+ construction users and worked on over $2 billion in built-environment projects. Based in New York with 51–200 employees, the company is growing with accelerating hiring velocity, particularly in engineering and sales roles.
Trunk Tools runs Kubernetes, Python, Go, and Node.js for backend infrastructure; React, TypeScript, and Webpack for frontend; and SageMaker, Ray, Prefect, Airflow, MLflow, Weights & Biases, and Arize for ML ops and model monitoring.
Active projects include multi-agent systems, intelligent document processing, knowledge graphs, Q&A AI agents, search capabilities, and third-party integrations—all aimed at automating construction workflows and reducing manual processes.
Trunk Tools'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.