AI-powered MES platform for pharma manufacturing compliance and traceability
Vimachem builds a modular manufacturing execution system (MES) for life sciences production, deployed across 200+ pharma sites globally. The stack—.NET + Angular frontend, PostgreSQL + MongoDB + TimescaleDB for time-series data, plus Azure infrastructure—reflects a mature IIoT platform handling batch digitization, equipment connectivity, and regulatory workflows. Hiring skews heavily toward senior engineers and product leadership across Bulgaria, Greece, and the US, signaling aggressive product expansion and customer delivery scaling rather than foundational build-out.
Notable leadership hires: Product Director
Vimachem develops a pharma-specific MES platform that digitizes batch records, integrates with production equipment, and enforces compliance workflows. The product is deployed across 200+ pharmaceutical and biotech sites, with modules covering AI-driven batch digitization, weigh-and-dispense connectivity, electronic logbooks, and equipment OEE tracking. The platform integrates with enterprise systems (ERP, CMMS, QMS, LIMS) and is marketed for rapid implementation (weeks, not months). The company operates from Queens, New York, with offices in Europe and distributed team members across 7 countries. Founded in 2014, Vimachem is ranked #1 MES on Gartner Peer Insights and recognized as a Great Place to Work multiple years.
.NET and Angular for the platform; PostgreSQL, MongoDB, and TimescaleDB for data; Azure for cloud infrastructure; RabbitMQ and MassTransit for messaging; Prometheus, Grafana, and New Relic for monitoring.
The Vimachem MES platform has been deployed across 200+ pharmaceutical and biotech manufacturing sites globally.
Vimachem - IIoT Pharma 4.0 AI Platform'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.