QuantEnt offers a platform that continuously analyzes users, roles, entitlements, and enterprise data as interconnected systems, applying mathematical models to certify access and detect exposure, drift, and structural risk.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often struggle to maintain accurate, up-to-date entitlement and data governance policies across complex, large‑scale identity ecosystems. Manual certification processes and rule‑based checks can miss entitlement drift, over‑exposure, and structural risks, leading to compliance gaps and potential security incidents.
Solution
QuantEnt provides a platform that continuously analyzes users, roles, entitlements, and data as interconnected systems, applying mathematical models to certify access and detect risk. By quantifying exposure, drift, and role integrity, the solution transforms periodic compliance checks into ongoing quantitative controls. Integrated with existing identity and IAM stacks, QuantEnt delivers real‑time alerts and actionable insights without requiring a replacement of current infrastructure. The platform also offers semantic data governance, automatically tagging metadata and enforcing cleanliness certifications to keep enterprise datasets organized and AI‑ready.
Target Audience
Primary customers are large enterprises in regulated industries—such as financial services, healthcare, and technology—that manage complex identity ecosystems and require robust data governance.
Features
- System‑level analysis of users, roles, entitlements, and data to identify interdependencies and hidden risks
- Quantitative certification engine that measures exposure, drift, and structural risk with mathematical rigor
- Continuous monitoring and real‑time risk detection alerts for entitlement over‑exposure and drift
- Seamless integration with existing IAM solutions, enhancing rather than replacing current identity stacks
- Semantic data governance tools that tag metadata, enforce data model rigor, and maintain ongoing data cleanliness
- AI‑native controls enabling safe agentic AI interactions with governed data and entitlement information