Monad
Working on building the first widely-available enterprise platform to help companies solve security challenges by accessing, unifying, and extracting the value hidden in existing security data.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor investor | €0.0 | round |
| investor | €0.0 | round | |
$17.0m | Series A | ||
| Total Funding | 000k | ||
| USD | 2022 | 2023 |
|---|---|---|
| Revenues | 0000 | 0000 |
| % growth | - | 13 % |
| EBITDA | 0000 | 0000 |
| Profit | 0000 | 0000 |
| EV | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 |
Source: Dealroom estimates
Related Content
Monad operates in the cybersecurity sector, focusing on providing enterprise-grade infrastructure for data-native security programs. The company offers a security data lake solution, which is a centralized repository designed to store, organize, and analyze large volumes of security data in its native format. This data can come from various sources, including structured data like databases and unstructured data such as plain text files. By leveraging big data technologies, Monad enables advanced analytics through machine learning and artificial intelligence to identify patterns and anomalies that traditional security solutions might miss.
Monad primarily serves enterprise clients who require robust security measures to protect their data. These clients span various industries, including finance, healthcare, and technology, where data security is paramount. The company operates in the cybersecurity market, which is characterized by rapid innovation and a constant need to address emerging threats.
Monad's business model revolves around providing a software-as-a-service (SaaS) platform. Clients subscribe to the service, gaining access to the security data lake and its advanced analytics capabilities. The company makes money through subscription fees, which can vary based on the volume of data processed and the specific features utilized by the client.
Keywords: cybersecurity, data lake, machine learning, artificial intelligence, enterprise, analytics, SaaS, security tools, data integration, threat detection.