Autonomous cloud storage optimization for AWS, Azure, and GCP
Lucidity builds autonomous optimization software for block storage across the three major cloud providers. The tech stack—AWS EBS, Kubernetes, eBPF, and deep storage instrumentation tools (fio, strace)—reflects a systems-level approach to real-time resource management rather than dashboard-only visibility. Hiring is weighted toward senior engineers (6 of 9 roles) paired with sales growth (3 roles), suggesting product-market fit in FinOps and moving from land to expansion.
Lucidity automates cloud storage optimization for FinOps, DevOps, and cloud infrastructure teams at enterprise scale. The platform works across AWS EBS, Azure, and GCP block storage, using policy-based controls and analytics to increase utilization 2–3x and reduce spend by up to 70% without requiring application changes or engineering effort. Founded in 2021, the company is based in New York with a 51–200-person team spanning engineering, sales, marketing, and support. Primary markets include financial services, retail, healthcare, and tech.
AWS, Azure, and Google Cloud Platform. Support covers block storage optimization across all three, with specific integration to AWS EBS.
Core infrastructure: Kubernetes, Docker, AWS EKS, Azure Kubernetes Service. Storage and observability: eBPF, fio, strace, Ceph, ZFS. Languages: Java, Python. Testing: Pytest, TestNG, Selenium, Playwright, JMeter.
Lucidity'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.