Visualization and debugging platform for robotics and autonomous systems
Foxglove builds a data visualization and debugging platform purpose-built for robotics teams. The stack reveals a deep investment in real-time data infrastructure: TypeScript + React frontend (Vite, WebGL, WebAssembly), Python + C++ + Rust for compute, Kubernetes orchestration, and inference pipelines (vLLM, Triton, TorchServe). Active projects span data ingestion, replay systems, and production fleet integration—signaling a shift from developer tooling toward production-grade infrastructure for autonomous systems at scale.
Foxglove provides an interactive platform for visualizing, debugging, and managing multimodal sensor data streams from robots and embodied AI systems. Founded in 2021 and based in San Francisco, the company serves robotics teams across commercial and defense sectors who need to understand how their systems perceive and respond in dynamic environments. The engineering-heavy organization (13 of 16 active roles) is actively scaling, hiring across the US, UK, Switzerland, and Australia, with most hires at senior and staff level—indicating a focus on building production infrastructure rather than early-stage features.
Frontend: TypeScript, React, Vite, WebGL, WebAssembly. Backend: Python, C++, Rust, Node.js, Go. Infrastructure: Kubernetes, AWS, GCP, Azure, PostgreSQL. ML/inference: vLLM, Triton, TorchServe, Pinecone, pgvector.
San Francisco, CA. Founded in 2021, the company is privately held with 51–200 employees.
Foxglove'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.