Tamnoon Unveils Managed Cloud Detection Response

Managed cloud security remediation provider Tamnoon announced today at AWS:reInforce its new managed cloud detection response offering. The company also unveiled Tami, an agentic AI solution designed to help organizations address inefficiencies related to the sheer volume of alerts to potential threats in their environment.

Channel Insider spoke with CEO and co-founder Marina Segal ahead of the announcement to learn more about the offering and how Tamnoon addresses customer pain points.

Security tool-agnostic solution is claimed to be an ‘industry-first’ 

Tanmoon was founded with a mission to optimize cloud security within existing environments. Now, it has released a new offering targeting the growing problem facing organizations: prioritizing, understanding, and remediating threat alerts at scale.

Built on AWS and launching with Wiz Defend, Amazon GuardDuty, Crowdstrike Falcon, and Orca Security, with more to come soon, the cloud security-agnostic service is already integrating with existing CNAPP offerings, providing runtime detection functionality. 

The company says this cross-platform capability enables Tamnoon to manage alert persistence for deprovisioned resources that would otherwise require manual intervention, while providing specific expertise in cloud-native concerns and delivering remediation in any format.

“There is no way you can come to market with a managed service offering that requires a replacement of existing systems,” Segal said. “You need to meet customers where they are and work within their existing environments.”

That work, Segal says, will dramatically improve how efficiently orgnizations can identify and act on potential risks flagged by these systems.

“We always want to determine what would happen if a fix is implemented before you take action,” Segal said. “You won’t get buy in from your development teams until you can determine that the fix wont break something else or cause other problems.”

“Our solution is to build to do three things:idenitfy the right plan for each customer’s unique environment, build the playbook for that solution with our models, all of which are trained on prior plans and successful actions, and then take what we learn to prevent the same issue from happening in the future,” Segal added.

“What makes our approach unique is that we don’t rely solely on deterministic rules or AI agents. Our system combines machine learning models trained on millions of cloud alerts triaged and fixed with human validation to avoid the false positives that plague fully automated systems,” said Idan Perez, CTO and co-founder of Tamnoon, in a press statement. “When we detect a potential threat, Tami performs an environment-aware analysis that considers your specific cloud architecture and business context before recommending action, which our human CloudPros then validate line by line before sharing with a customer.”

This is where an agentic AI-enabled solution like Tami will make the most difference, Segal says, in ensuring that alerts are handled at scale.

“In situations where there is not a deterministic yes/no path, that’s where we still require human intervention,” said Segal. “We have developed the ability to create human-centric models that bring interaction in at the moments that are best suited for human reasoning.”

This model, Segal says, allows teams to more clearly and effectively prioritize which of their various alerts require attention and which can be at least started autonomously. All of this means more time saved, and ultimately a better security posture, for organizations leveraging Tamnoon.

Tamnoon’s research points to the growing need for MDR process in cloud threats

According to Tamnoon’s 2025 State of Cloud Remediation Report, over 35% of all alerts are classified as critical or high, with critical alerts taking almost a year to resolve.

CDR alerts are especially resource-intensive because they persist until manually reviewed and require an active resolution decision. What may begin as 5–10 unreviewed alerts can quickly escalate to 100 or more, introducing alert fatigue and operational bottlenecks and hiding active critical threats.

“Security teams are drowning in cloud alerts with no easy way to determine which ones need immediate attention,” said Travis Farral, VP and CISO at Archaea Energy, in a press statement. “Teams are looking for a way to quickly distinguish between routine operations and genuine security concerns in the context of their unique environment.”​​​

“I think this is aligned with what the industry is headed towards as there is more consolidation between the worlds of CNAPP and CDR work,” Segal said. “This offering will allow us to work more closely with SOC teams and bring value to them.”

At the same time, Tamnoon is adamant that technology has not (yet, at least) evolved enough to remove human involvement from the process entirely. In the meantime, the company promises to solve customer pain points with a blend of technology and human expertise.

“We work to make a variety of platforms and solutions operational to help customers take control of their environments,” Segal said.

Cloud-based threats pose a significant concern for many managed service providers (MSPs) and their customers. Catch up on the latest news and industry trends with our coverage.