Mimica maps how enterprise employees work at the desktop and turns that activity into process maps that pinpoint automation targets. Its stack pairs Python/FastAPI and TypeScript/React with RAG and Transformer tooling on Kubernetes across AWS and GCP, and active work on real-time graph-editing backends and a chatbot evaluation framework suggests a GenAI layer on top of the mapping engine. Hiring is engineering-heavy with a strong senior and staff skew.
Notable leadership hires: Product Head
Mimica is a London-headquartered, privately held software company founded in 2018, with 201–500 employees. It sells task mining and process intelligence to large enterprises that want to find where to standardize or automate work. The product records desktop activity, builds process maps, ranks improvements by return, and recommends automation approaches such as RPA, document processing, or GenAI. Hiring spans the United States, Canada, Latin America, the UK, and much of continental Europe, and the go-to-market team works in Salesforce, Outreach, and LinkedIn Sales Navigator.
Mimica runs Python with FastAPI, Node.js, TypeScript, and React, on Kubernetes (AWS EKS) with Terraform and ArgoCD. It uses PostgreSQL and MongoDB, with Grafana, Prometheus, Loki, Tempo, and Honeycomb for observability.
Mimica hires in the United States, Canada, the UK, Ireland, Costa Rica, Brazil, Argentina, Czechia, Poland, Portugal, the Netherlands, Germany, Sweden, and Estonia.
Current work includes a real-time backend for graph data editing, scaling the Mimica platform backend, real-time frontend services, an ML integration API library, and a framework for evaluating chatbot output quality.
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Mimica'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.
