Overview
- Eliminate alert fatigue by having Tami automatically aggregate data and conduct deep investigations across your CNAPP or CDR, so you focus only on critical decisions
- Stop guessing which fix is safe with human-verified remediation plans generated by Tami’s CloudPros process, ensuring zero outages when you act
- Resolve unique risks in any cloud context—single, multi, or hybrid—as Tami generates provider-specific, validated fixes tailored to your environment
- Accelerate response to novel threats as Tami’s Code Generation Agent learns from Tamnoon’s expert playbooks and creates innovative approaches where no existing solution exists
- Maintain full control over remediation execution because Tami’s Automation Retriever Agent selects and runs the right automation, then analyzes the result for you
- Scale security operations without adding headcount by letting Tami’s four integrated agents orchestrate and execute remediation plans under expert supervision
Pros & Cons
Pros
- Cloud security enhancement
- Data aggregation capability
- In-depth risk investigation
- Context-aware technology
- Supports CNAPP and CDR
- Orchestrates remediation plans
- Agent diversification
- Automated response formulation
- Human verification process
- Training on Tamnoon's playbooks
- Versatile multi-cloud support
- Flexible hybrid cloud support
- Provider-specific remediation steps
- Facilitates agent-led remediation
- Creates innovative solutions
- Safe remediation focus
- Proficient in different contexts
- Collaboration with expert supervision
- Learn from best practices
- Automatically creates validated fixes
- 24/7 Cloud SOC support
- Tool-agnostic security
- Full-cycle remediation
- Agentic cloud security capability
- Backed by human experts
- Detailed Reporting and Compliance
- Agentic Investigation
Cons
- Dependent on multiple agents
- Needs human verification process
- Trained only on Tamnoon's playbooks
- No specified support for non-CNAPP/non-CDR
- Consists mainly of non-generic LLMs
- Heavy reliance on expert supervision
- No clear onsite continuous learning
- Fixed, limited models utilization
- Not identifiable multi-cloud support details
- Non-disclosed solution for single-cloud context
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❓ Frequently Asked Questions
Tami's main function is to aggregate data, conduct deep investigations, and generate remediation to support cloud security engineers focusing on safe remediation.
Tami supports companies using a CNAPP or CDR by handling day-to-day security tasks. It assists in aggregating data, conducting deep investigations, and generating remediation, thus enabling the companies to maintain a safe network environment.
Tami is composed of four different agents with specific roles. The 'Context Agent' is the main orchestrator of initiatives. 'External MCP Agent' communicates with external CNAPPs and CDRs using the MCP protocol. The 'Code Generation Agent' learns from Tamnoon's experts and playbooks, then expands on its own. Lastly, the 'Automation Retriever Agent' selects or creates the automation to run and then analyzes the result.
Tami uses multiple Language Models (LLMs) that are selected for specific tasks. These models may be trained on Tamnoon's two million-plus remediations or can be generic LLMs with deep guardrails. While the main action is carried out by the trained model, secondary models quality assure the output to meet Tamnoon's standards.
The CloudPros verification process in Tami is a human verification procedure designed to ensure the logic and safety of proposed solutions. This system enables Tami to resolve numerous alerts without causing any outages.
Tami tackles response formulation in cloud security by automatically creating detailed, contextual, and validated fixes for any risk it encounters. This innovative approach solves the industry's challenge of having powerful detection tools but struggling with formulating responses.
Tami has been trained on Tamnoon's playbooks, written by CloudPros who specialize in major cloud providers, CNAPPs, and CDRs. These playbooks allow Tami to learn from best practices, thus enabling it to innovate and tackle unique scenarios where no exact solution is available.
Tami operates proficiently in different cloud contexts--whether single-cloud, multi-cloud, or hybrid-cloud. It generates thorough, provider-specific remediation steps for each unique context.
Agent-led remediation in Tami refers to the process of navigating and solving security challenges under the guidance and oversight of Tami's four integrated agents. This process is supplemented with artificial intelligence to achieve safe remediation and effectively enhance cloud security.
The specific tasks that Tami's Language Models are selected for involve mainly the aggregation of data, deep investigation, and remediation generation in the context of cloud security.
Tami enhances cloud security by creating validated fixes for any risk it encounters. It reduces the vulnerability of the cloud by conducting deep investigations and automatically responding with expert-directed remediations.
Tami automatically creates validated fixes for the risks it encounters by applying its trained language models to analyze the risk, formulate an appropriate response, and validate its effectiveness before implementation.
Tami creates innovative approaches in unique scenarios where no exact solution exists based on its training from Tamnoon's playbooks and the continuous learning from new situations and challenges.
Tami supports multi-cloud and hybrid-cloud contexts by being able to work proficiently and generate comprehensive, provider-specific remediation steps regardless of the cloud context.
Provider-specific remediation steps provided by Tami are detailed, contextual, and validated fixes designed to effectively resolve security risks in any unique cloud context, including single, multi, or hybrid-cloud environments.
Yes, Tami can work proficiently in a single-cloud context. It's designed and trained to operate efficiently in different cloud contexts, including single-cloud, and to generate comprehensive, provider-specific remediation steps.
Expert supervision plays a critical role in Tami’s operation. It ensures that Tami's automated responses are logical, safe, and effective, all the while allowing Tami to resolve numerous alerts without outages. This fusion of artificial intelligence and human expertise empowers Tami to continuously improve and adapt to new challenges.
Tamnoon’s playbooks play a critical role in training Tami as they provide a wealth of best practices and expertise from CloudPros. This enables Tami to learn, adapt, and create innovative solutions for unique cloud security challenges, thereby enhancing its capabilities.
Tami aids cloud security engineers by taking over day-to-day security tasks. It allows engineers to focus on their crucial role of providing safe remediation. It does so by aggregating data, conducting deep investigations into security issues, and generating remediation plans.
Tami handles everyday security tasks by using artificial intelligence to automatically aggregate and analyze data, conduct in-depth investigations into security alerts, and generate remediation plans.
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