Gamma offers an AI‑driven cloud data loss prevention platform that discovers and classifies sensitive data across all SaaS applications, devices, and users with 99.5% accuracy using deep‑learning and NLP. Its off‑path, one‑click deployment requires no network or endpoint agents and provides real‑time, context‑aware remediation prompts to reduce insider‑related breaches. The solution integrates with existing security tools and supports both cloud and on‑premise applications for enterprise‑scale data protection.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations increasingly rely on a growing number of SaaS applications, while employees frequently use personal devices for work. This creates extensive, hard‑to‑monitor data flows across cloud services, leading to a high incidence of data breaches that often start with human error or insider misuse.
Solution
Gamma provides an AI‑driven cloud data loss prevention (DLP) platform that discovers and classifies sensitive data across all sanctioned SaaS applications, devices, and users with 99.5% accuracy. Its deep‑learning models analyze content—including images, handwritten notes, and complex documents—to identify PII, PHI, PCI, intellectual property, and other confidential data without relying on static regex rules. The solution operates off‑path, requiring no complex network or endpoint integration, and can be deployed in minutes across the entire cloud stack. Users receive real‑time remediation prompts, enabling instant corrective action and reducing false positives. Gamma’s analytics integrate with existing security tools and can complement legacy DLP solutions, delivering continuous risk reduction and compliance monitoring.
Target Audience
Primary customers are enterprises and fast‑growing startups that use multiple SaaS platforms and need a scalable, easy‑to‑manage DLP solution to protect sensitive data and reduce insider‑related risk.
Features
- 99.5% accurate data classification using advanced deep‑learning and NLP techniques
- Automatic detection of sensitive data in images, handwritten notes, and complex document types
- Context‑aware analysis that distinguishes sensitive from non‑sensitive usage to minimize false alerts
- One‑click deployment across all cloud applications (e.g., GSuite, O365, Slack, Box, Salesforce, GitHub, Jira) and user devices
- Off‑path architecture that requires no network or endpoint agents and integrates with existing DLP solutions
- End‑user remediation interface that empowers employees to resolve violations instantly
- Support for on‑premise applications in addition to cloud services