In cybersecurity, speed is everything. The longer you wait to integrate and act on your data, the more room you leave for threats to slip through the cracks. Yet, many security operations centers are stuck in neutral thanks to outdated SIEM onboarding processes that can take upwards of six months or more. That’s not just inefficiency; it’s a direct risk to your enterprise.
Let’s face it: traditional onboarding is a slow-motion disaster. Some reports show organizations are juggling 70 to 90 security tools, each pumping out logs in different formats. Manually parsing and integrating these sources requires costly expertise, creates blind spots, and pushes your time-to-value months down the road. While you’re still configuring connectors and writing regex rules, your adversaries are already moving laterally in your network.
Industry data reveals a painful truth: delayed visibility translates into inflated breach costs. Threats that linger undetected cost millions more to contain. The Ponemon Institute puts the average breach lifecycle at 258 days, with prolonged onboarding contributing to that extended window. And for insider threats? The cost of incidents taking more than 90 days to contain can soar past $18 million.
The financial hit doesn’t stop there. There’s also delayed ROI. Security investments should yield fast, actionable results vs. taking half the year for implementation. When your SIEM isn’t ready to deliver, budget justifications get harder, and the business loses confidence in your program’s value.
Gurucul turns that six-month waiting game into a short sprint. Our AI-driven SIEM pipeline management slashes onboarding timelines from months to days. With pre-trained Agentic AI, we make log ingestion plug-and-play even across highly diverse data sources. And with our Generative AI-powered parsing engine, we eliminate the need for manual rule-writing and regex gymnastics. Logs come in, context is understood, and data is parsed in minutes.
The result? Security outcomes in days, not quarters. Blind spots eliminated. Analyst time redirected toward threat detection and remediation instead of regex debugging. And most importantly real protection, delivered on time.
If your SIEM is still onboarding while adversaries are already exfiltrating data, you’re not just behind—you’re exposed. Gurucul’s AI-powered SIEM is engineered to collapse time-to-value and elevate your security posture in record time. It’s not just an upgrade; it’s a transformation.
Traditional onboarding relies on manual configurations, custom connectors, and regex-based parsing—all of which can take months, especially when dealing with dozens of diverse security tools. This labor-intensive approach can take months. In contrast, an AI SIEM like Gurucul automates ingestion and parsing with Agentic AI and Generative AI, reducing setup time from months to days and often delivering data visibility in under 24 hours.
Delays create blind spots, increasing the risk of undetected breaches. The longer a threat lingers, the more it costs—up to $18M for insider threats taking 90+ days to contain.
Gurucul uses Agentic AI to simplify ingestion and Generative AI to parse raw logs in minutes. Core data sources can be onboarded in as little as a day. Gurucul’s AI threat detection is a cutting-edge cybersecurity approach that leverages artificial intelligence (AI) and machine learning algorithms to identify, analyze, and respond to potential security threats in real-time.
Gurucul offers rapid custom connector development in 48–72 hours, ensuring even unique data doesn’t stall your deployment timeline.
