Autonomous block storage optimization platform for AWS, Azure, and GCP
Lucidity automates cloud storage management using a stack built on Java, Python, AWS, Azure, and GCP primitives (eBPF, strace, iostat, EBS), with heavy testing infrastructure (Pytest, TestNG, JMeter, WireMock). The hiring acceleration (11 roles in 30 days, balanced 7 engineers / 7 senior roles) combined with active projects spanning automated scaling, test frameworks, and CI/CD pipeline buildout signals a company moving from MVP toward production hardening and sales motion — the project list includes both platform depth (filesystem corruption simulation, API testing) and go-to-market velocity (enterprise and mid-market outreach programs).
Lucidity provides autonomous optimization for block storage across major cloud providers, targeting FinOps, DevOps, and Cloud Infrastructure teams at enterprises. The platform delivers real-time storage analysis and policy-based optimization without requiring changes to existing cloud environments. According to the company, customers typically see 2–3x utilization increases and up to 70% cost reductions, with hundreds of engineering hours freed from manual storage management. The product is deployed across financial services, retail, healthcare, and technology verticals.
Lucidity optimizes block storage across AWS, Azure, and Google Cloud (GCP). The platform uses cloud-native primitives including AWS EBS, and operates with zero changes to customer environments.
Core: Java, Python, AWS, Azure, GCP. Testing & diagnostics: Pytest, TestNG, JMeter, WireMock, eBPF, strace, iostat. Infrastructure: Docker, Spring Boot, Linux, Windows, MySQL, Ceph, ZFS.
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