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How MSSPs and MDRs Can Maximize Threat Detection Efficiency with Uncoder AI
- Managing detection rules across multiple security solutions in the environments of current and potential clients poses a significant challenge to service providers.
- Detection engineers, SOC analysts, and SIEM administrators in MDR/MSSPs face daily challenges managing detections across diverse client infrastructures.
- A vendor-agnostic approach to detection engineering might greatly simplify the process.
- Tools like Uncoder AI significantly ease the amount of manual work required to maintain detection efficiency by enabling engineers to convert detection logic across various SIEM formats quickly.
- Relying heavily on manual work in multiple processes can lead to errors, inefficiencies in detection, and other bottlenecks in the detection pipeline.
- Uncoder AI enables teams to leverage automation capabilities to quickly and seamlessly translate detection rules across various SIEM platforms.
- Minimizing the Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) metrics is crucial for demonstrating the effectiveness of their services.
- With Uncoder AI, detection engineers can swiftly generate SIEM-specific queries from raw IOCs and further simplify the process by applying the custom data schema and automated deployment by their choice.
- Using Uncoder AI, teams can streamline the routine processes of translating and customizing generic detection rules into 44 SIEM, EDR, XDR, and Dala Lake technologies.
- Uncoder AI greatly simplifies the process of adapting the detection logic from one SIEM format to another by automating cross-platform translations.
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