Nightfall AI

Nightfall AI

Nightfall identifies business-critical data across SaaS, APIs, and data infrastructure so it can be managed and protected. Learn more

Financials

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Revenues, earnings & profits over time
USD20192020202120222023
Revenues1.4m3.6m7.1m13.6m29.5m
% growth-167 %98 %91 %117 %
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Recent News about Nightfall AI

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Nightfall.ai is a cutting-edge startup specializing in data leak prevention (DLP) for SaaS (Software as a Service) and cloud environments. The company leverages artificial intelligence (AI) to help businesses identify, classify, and protect sensitive data. This is crucial in today's digital landscape where data breaches and cyber threats are increasingly common.

Nightfall.ai serves a diverse range of clients, including large enterprises and tech companies that use platforms like Slack, Google Drive, GitHub, Confluence, Jira, Salesforce, Asana, and Zendesk. These clients operate in various sectors but share a common need to safeguard their sensitive information, such as credit card numbers, personal identification details, and other confidential data.

The market Nightfall.ai operates in is the cybersecurity sector, specifically focusing on data protection and leak prevention. This market is growing rapidly due to the increasing number of cyber threats and the expanding use of cloud services.

Nightfall.ai's business model is based on providing API (Application Programming Interface) integrations that allow developers to embed data security features directly into their applications. Clients can create custom detection rules and use Nightfall's AI-powered detection engine to scan and protect their data. The company generates revenue through subscription fees for access to its APIs and additional services.

In summary, Nightfall.ai is a vital player in the cybersecurity market, offering AI-driven solutions to help businesses protect their sensitive data in cloud and SaaS environments. By providing customizable API integrations, the company enables clients to build robust data security measures into their applications, ensuring compliance and reducing the risk of data breaches.

Keywords: Data Leak Prevention, AI, Cybersecurity, SaaS, Cloud, API Integration, Sensitive Data, Data Classification, Subscription Model, Custom Detection Rules.

Tech stack

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