Cymphology provides a security platform that unifies data, identity, and behavior signals across collaboration tools, creating a real‑time Human Graph to detect over‑exposure, abnormal file activity, and identity hygiene gaps. The solution offers AI adoption controls, file and identity risk management, automated data labeling, and extended workforce oversight to continuously monitor and remediate human‑related cyber risks.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations adopting AI and using collaboration tools face increasing human-related cyber risks, such as over‑exposure of sensitive data, abnormal file activity, and gaps in identity hygiene. Traditional security solutions often treat data and identity separately, making it difficult to detect and remediate these intertwined risks.
Solution
Cymphony delivers a human‑centric security platform that unifies data, identity, usage, and behavior signals across collaboration environments. By constructing a dynamic “Human Graph,” the platform maps file sharing, AI‑driven data access, and identity posture in real time, providing a single risk layer that highlights over‑exposure, abnormal file actions, and identity hygiene gaps. Integrated AI adoption controls, file risk management, and identity risk management modules enable continuous monitoring and automated remediation. The solution also offers data labeling capabilities to improve the handling of unstructured data and extended workforce oversight to protect contractors and partners. This unified approach helps enterprises secure the human element while confidently deploying AI technologies.
Target Audience
Primary customers are mid‑size to large enterprises that rely on collaborative platforms and are actively adopting AI, particularly security, compliance, and IT teams responsible for data protection and identity governance.
Features
- Human Graph that maps data flow, file sharing, and AI‑powered access across native and third‑party collaboration tools
- AI Adoption risk module that identifies over‑exposure and monitors usage of AI models on sensitive data
- File Risk Management that detects excessive sharing, abnormal file activity, and unauthorized access
- Identity Risk Management with continuous assessment of access privileges, role alignment, and identity hygiene gaps
- Data labeling engine that automates classification of unstructured data to support AI and compliance workflows
- Extended Workforce Oversight for monitoring contractors, partners, and other non‑employee identities
- User and Entity Behavior Analytics (UEBA) that correlates user actions with data and identity contexts to surface anomalous behavior