Nightfall launches ‘Nyx,’ an AI that automates data loss prevention at enterprise scale

Nightfall Ai launched the first platform to prevent autonomous data loss in this field, as an AI agent automatically searched for security incidents and rhythm policies without human intervention – a breakthrough that can reshape how institutions protect sensitive information in the era of expanding cybersecurity.

NYX Night Flage Night Night Night in San Francco represents a basic transformation of traditional data loss tools (DLP) that depends on handicrafts and generating high amounts of wrong alerts. Instead, the regime uses the agent of Amnesty International to reflect the work of security analysts, give priority to threats automatically and distinguish between legitimate commercial activities and real security risks.

“Security teams are drowning in alerts while advanced threats from within via ancient DLP systems decline,” said Rohan Satti, CEO and co -founder of Nightfall. “When analysts spend hours in investigating false positives only to discover that real threats have not been discovered because they do not match a pre -determined pattern, organizations not only lose time – they lose control of their most sensitive data.”

This advertisement comes at a time when companies are struggling with the explosion of the security safety challenges that work driven away and adopt the cloud and the rapid spread of artificial intelligence tools in the workplace. The global cybersecurity market, which is worth about $ 173 billion in 2023, is expected to reach $ 270 billion by 2026, while protecting data that is a large part of this growth.

How to cut the discovery that works with artificial intelligence system false alerts from 80 % to 5 %

Traditional DLP systems have long thwarted security teams because their accuracy rates may reach 10 to 20 %, according to Sathe. These old platforms depend greatly on matching patterns and regular expressions to identify sensitive data, creating a fixed stream of wrong alerts that require manual achievement.

“It has ended with the employment of the SOC analyst to overcome all the wrong positives,” Satti explained. “With an Amnesty International Classification approach, you can get it to 90, 95 % of accuracy.”

Nightfall NYX combines three AI’s energy -powered components: advanced content classification using large language models (LLMS) and computer vision, and track data rates that understand where information arises and travels and improves independent policy that learn from the user’s behavior over time.

Satti said that the platform artificial intelligence agent sits on top of the detection infrastructure and “mainly reflects what DLP SOC analyst will do.” “Looking at all accidents on the surface in Nightfall in the dashboard, then submit recommendations about what must be investigated urgently, then what is the policy modification that must be done to distinguish the real workflow versus things that are already dangerous.”

The statute reaches where institutions face a new category of data risk: “Shadow AI”, where employees use unauthorized AI tools such as ChatGPT, CLADE or Copilot for work tasks, and they often offer information about the sensitive company unintentionally.

Unlike the traditional DLP solutions that depend on allowing fixed applications or essential content, Night Fall picks up the actual content that has been affixed, written or downloaded on AI tools, as well as the data rates that show where the information has arisen. The system can monitor reactions at the rapid level across the main AI platforms including ChatGPT, Microsoft Copilot, Claude, Gemini and Perplexity.

“It is a small dead, because artificial intelligence determines the risk of using artificial intelligence.” The statute analyzes the common content with artificial intelligence applications and paths in which it originated and determining whether the patterns of use are a natural commercial activity or possible security violations.

Customer accreditation increased, with accuracy rates 95 % through institutions deployment operations

Nightfall’s approach has gained a traction among institutions looking for alternatives to old solutions from Microsoft, Google and other traditional cyber security sellers. The company is now serving “hundreds of customers and operations” hundreds of TERABYTES daily “of data through publishing operations that support more than 50,000 employees, according to Sathe.

Aaron furniture retail stores embody the customer value. The company had previously struggled with the old DLP solution, which was born of excessive false pros and cons of Slack. After spreading dark solutions, “they were like,” Wow, we can really reduce the time when we need to investigate all these things, “because most of all that you float is legitimate,” Sashi said.

Rapid adoption reflects the broader frustration in the market with traditional methods. Within six months of the launch of DLP capabilities at the end point, Nightfall has made a 20 % penetration between its current customer base-a metric scale that was highlighted as evidence of the suitability of the strong products market.

DLP LEGY sellers face a disruption from independent security platforms

Nightfall is competing against well -known players, including Microsoft PurView, which combines Enterprise Office 365 licenses, as well as dedicated DLP sellers such as ForcePoint, Symantec and Awter Contriculations. However, SATHE argues that combined solutions have hidden costs in the form of human workers needed to manage false positives.

“Employing people, training them and saving time on DLP when they can do something else, from the point of view of the alternative opportunity cost is dollars at the end of the day,” Sat said.

Light architectural engineering provides the company, which uses API integration instead of network agents, to publish faster compared to traditional solutions that may require three to six months to implement. Night Fall Value customers usually see within weeks instead of the most famous, according to Sathe.

Lightweight architecture provides for weeks for months

Central in the Nightfall distinction is the original AI structure. Although old systems require widespread manual control to reduce the wrong positives, Nightfall employs automatic learning models (ML) that automatically improves through what the company calls “learning subject to overseeing illustrative comments”.

The statute maintains the potential for “allocated detection” similar to the recommendation algorithms used by Tiktok or Instagram, which leads to the creation of forms dedicated to each institution based on the specified data patterns and user behavior. This approach allows the system to distinguish between routine commercial activities and real security threats without a widespread manual composition.

The publishing model confirms the implementation without friction through the light ending point agents and API integration with famous Saas applications. This contrasts sharply with traditional DLP solutions that often require changes in the complex network infrastructure and long seizures.

65 million dollars in financing the goals of the industries subject to the hungry to protect intellectual property

Night Fall raised about 65 million dollars of financing and reports strong financial position because it targets organized industries including health care, financial services, technology, legal and manufacturing. The company sees a special opportunity among organizations that deal with intellectual property protection, as it fights traditional DLP solutions to identify and protect royal information.

The opportunity of the broader market reflects the intersection of many technology trends: the continuation of deportation to the workflow based on the group of the orbits, the explosion of the adoption of the artificial intelligence tool in institutions and the increase in organizational audit on data protection. The recent prominent data and threat incidents of the interior have raised the prevention of data loss as a lifestyle at the board of directors of many organizations.

The future of cybersecurity: Independent factors are replaced by manual security operations

With institutions continuing to adopt artificial intelligence tools with ratification with the requirements of advanced data protection, solutions that can automatically adapt to new threats while reducing operational expenditures to the following development in the security of the institutions. Nightfall’s early success indicates that the market is ready for the most intelligent and independent approach to data security that exceeds the limits of traditional regulations based on rules.

The statute’s ability to provide contextual accident summaries – such as “the employee has been uploaded to a file containing 200 PII records from the client from Salesforce to Google Drive while working a distance” – represents the type of implementation intelligence that security teams need to respond effectively to threats.

The company’s focus on eliminating the manual control burden, which has long been plagued by DLP publishing operations, addresses a basic pain point for adopting data protection techniques. If it succeeds, this approach can accelerate the adoption of institutions for comprehensive DLP programs and raise the general security position through industries that deal with sensitive information.

The shift towards independent security operations reflects a broader transformation through institutions’ programs, as artificial intelligence agents are increasingly dealing with tasks that require human experience. As for the industry that is struggling through fatigue from warning and resource restrictions, the promise to protect independent data may finally provide the long -term goal for the speed that works with business.