AI-powered lab supply marketplace automating procurement for life-science R&D
ZAGENO operates a two-sided marketplace connecting labs to 50M+ products from 6,000+ suppliers, with AI driving personalization, pricing optimization, and supplier intelligence. The tech stack—Python, TensorFlow, PyTorch, Spark, Kafka, Kubernetes—reflects a machine-learning-first architecture. Active hiring is concentrated in senior engineering and product roles across India, paired with projects in recommendation systems and search optimization, suggesting aggressive scaling of the intelligence layer feeding the platform.
ZAGENO is a procurement platform for life-science research labs, simplifying the sourcing and ordering of research consumables and reagents. The company operates a marketplace of 50M+ products from over 6,000 global suppliers, enabling labs to consolidate ordering, automate compliance workflows, and gain real-time visibility into spend and delivery. Founded in 2015 and headquartered in Cambridge, Massachusetts, ZAGENO serves labs of all sizes with offices in Europe and Asia. The business targets the friction and administrative overhead that pulls scientists away from research.
ZAGENO uses Python, TensorFlow, PyTorch, Apache Spark, Kafka, and Kubernetes for its core platform, with PostgreSQL, Elasticsearch, and MongoDB for data storage, and FastAPI/Django for backend services. AWS, GCP, and Azure provide cloud infrastructure.
Current projects include AI-powered recommendation systems, search and discovery optimization for scientists, pricing optimization models, supplier intelligence analytics, and backend scalability improvements for mid-to-large scale features.
ZAGENO Inc.'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.