Mathematical optimization solver for enterprise decision automation
Gurobi builds the core solver engine for complex optimization problems across 40+ industries, with over 1,200 customers relying on it for supply-chain, pricing, and resource-allocation decisions. The tech stack reveals a sharp pivot toward AI integration—Anthropic, OpenAI, AWS Bedrock, LangChain, and LangGraph sit alongside the core optimization engine—while sales hiring (6 roles) outpaces engineering (3), signaling aggressive enterprise land-and-expand motion paired with API-first SaaS delivery (Gurobot agent, Cloud AI integration projects).
Notable leadership hires: Sales Director
Gurobi Optimization develops mathematical optimization solvers for enterprises solving large-scale integer programming, linear programming, and quadratically constrained problems. The product runs standalone or integrated with machine learning and AI workflows. Founded in 2008 with headquarters in Beaverton, OR, Gurobi operates across the USA, Europe, and Asia and employs 51–200 people. Active development focuses on cloud delivery (SaaS instant cloud, Compute Server AI integration), agent-based interfaces (Gurobot), and automation of internal revenue operations—reflecting both customer-facing product maturity and internal scaling friction around billing, contracting, and deal velocity.
Gurobi's stack spans optimization (C++, Java), enterprise integration (Salesforce, MuleSoft, NetSuite), and emerging AI (Anthropic, OpenAI, AWS Bedrock, LangChain). Python, Go, Node.js handle application logic; React and JavaScript front the UI.
Gurobi employs 51–200 people, headquartered in Beaverton, OR, with operations in the USA, Europe, and Asia.
Gurobi Optimization'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.