Work operating system for orchestrating AI agents and enterprise workflows
Reejig builds infrastructure for deploying AI agents into enterprise work processes. The stack—Python, LangChain, PyTorch, RAG, React, AWS—reflects a company focused on AI orchestration and workflow design rather than general SaaS tooling. Active projects span AI-powered design engines, workforce transformation journeys, and multi-platform content workflows, while pain points cluster around AI adoption velocity and time-to-value—suggesting Reejig is solving the implementation and change-management gap that enterprises hit when moving from pilot to production AI.
Reejig is a work operating system designed for enterprises deploying AI agents into business processes. Founded in 2019 and based in New York, the company targets Fortune 50 enterprises and mid-market organizations looking to orchestrate heterogeneous agent stacks, track agent performance in real workflows, and operationalize AI at scale. The platform unifies work architecture (how jobs and tasks are designed), work context (data and skills), and AI orchestration on a single system. Sales and implementation are geographically distributed across the US, Australia, and Canada.
Python, LangChain, PyTorch, and RAG for AI; React and Vue for frontend; Node.js for backend; AWS (EKS, ECS, Terraform) for infrastructure; plus OpenAI, Copilot Studio, and HubSpot for integrations.
AI-powered design engines and workflows, workforce transformation programs, post-sale implementation journeys, video and multi-platform content workflows, and community engagement. Projects focus on reducing time-to-value for AI adoption.
Reejig'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.