US startup Clario has launched from stealth with $US6 million in seed funding, targeting the redundant, obsolete and trivial files that clog enterprise systems.
The company connects to platforms including Google Drive, SharePoint, OneDrive, Box and Confluence. It scans metadata to surface low-value data, then prompts staff through Slack or Teams to keep, archive or delete each file.
Clario says it charges only when a customer makes one of those decisions, and that the system learns from them over time to automate cleanup.
Over time, Clario learns from these decisions to build an autonomous system that routinely cleans, organizes, and maintains unstructured data.
The pitch targets a measurable problem. Clario cites industry estimates that 78 per cent of stored enterprise data is unstructured, with more than a third effectively garbage.
It also points to a Gartner forecast that 60 per cent of AI projects will be abandoned this year due to poor data quality.
“Garbage in, garbage out isn't a cliche, it's an incredibly costly mistake,” said Yousuf Khan, co-founder and chief executive of Clario.
“Companies are burning real money on tokens by throwing terabytes of garbage data into AI projects that promise revolutionary results. It isn’t working. This is one of the industry’s most ubiquitous and challenging problems, and Clario is the first product purpose-built to solve it.”
Khan, a five-time chief information officer turned investor, founded Clario with Madhu Vohra, a former engineering leader at Oracle, NetApp, Nutanix and VMware.
“This problem isn’t going away, it’s only compounding. The first wave of AI tools have caused the volume of unstructured data to increase at an exponential pace, with no slow-down on the horizon,” said Madhu Vohra, Co-Founder & CTO, Clario.
“Enterprises cannot afford to further dilute precious resources like storage and compute, already taxed by the demanding requirements of AI and LLMs. The time to build a clean data foundation is now.”
The company claims to be the first product purpose-built to eliminate data ROT, though established data-governance and storage vendors address adjacent problems. Early customer scans surfaced terabytes of waste, including obsolete file formats and feature-length films left by former staff.