Data, AI, and customer value management consulting and platforms
Exacaster is a data and AI consulting firm built around three service lines: data management, AI acceleration, and customer value management (CVM). The engineering-heavy hiring mix—11 of 16 active roles—and deep project focus on infrastructure automation (Terraform, Ansible, Kubernetes) and vector/generative AI systems signal a shift from pure advisory toward platform delivery. Internal pain points around delivery governance, stability at scale, and QA gaps suggest they're scaling delivery rigor as client workloads grow more complex.
Founded in 2011 in Vilnius, Exacaster began with predictive churn models for telecom and has expanded to serve organizations across 16+ countries in finance, insurance, logistics, utilities, and retail. The firm operates as a three-pillar service provider: data management (strategy, architecture, and ongoing platform support across AWS, Azure, GCP, and on-premises), AI acceleration (generative AI applications, agentic systems, and knowledge bases), and customer value management (proprietary CVM Platform handling customer data, decisioning, campaign orchestration, and churn prediction). The CVM platform currently manages engagement for 13M+ subscribers and has helped customers manage $43B in customer lifetime value. Exacaster serves customers that require end-to-end data architecture, large-scale infrastructure, and vertical expertise—particularly in telecom and financial services.
Exacaster uses AWS, Azure, and GCP for cloud infrastructure; Cloudera for big data; Kubernetes for orchestration; Python, SQL, and dbt for data work; LangChain, Claude, and GPT for AI; and Prometheus, Zabbix for monitoring. Terraform and Ansible handle infrastructure automation.
Exacaster serves telecom, finance, insurance, logistics, utilities, and retail across 16+ countries. The firm has particular depth in telecom (its founding vertical) and financial services, where it handles large-scale data platforms and governance-sensitive workloads.
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