Abstract is a pioneer in streaming, first security data operations and has revealed the launch of AI, Gen Composable SIEM, an advanced security information and event management platform that is entirely AI, streaming of real, time data and adaptable security workflows compliant.
This strategic release follows an exceptional year of growth for Abstract, marked by:
- 380% year-over-year ARR increase,
- 280% growth in new customer acquisitions,
- 264% net revenue retention,
- And 40 strategic hires to bolster enterprise expansion.
Due to the tremendous increase in global security data the volume is expected to grow by 25, 30% every year driven by AI telemetry and multi, cloud complexity, a traditional SIEM has basically hit a wall. AI, Gen Composable SIEM sets a fresh architectural benchmark by adopting a streaming, first methodology, whereby each element of the puzzle, i. e. data ingestion and pipelines, storage, detection, AI triage, and automated response can operate as separate, composable units and thus work together.
A New Architectural Paradigm for SIEM
AI-Gen Composable SIEM is built to support flexible, high-velocity security operations without the limitations of monolithic platforms. Key capabilities include:
- Decoupling data sources and destinations to eliminate vendor lock-in
- Running threat detections in-stream for real-time response
- Intelligently tiering and routing data to optimize storage costs
- Embedding AI across workflows for triage, investigation, and response
- Scaling elastically across hybrid and multi-cloud environments
This composable approach gives enterprises the freedom to select their preferred architecture, deployment model, and analytics engines without compromising performance or control.
Also Read: CrowdStrike Advances SOC Automation with Next-Generation Falcon Fusion SOAR Enhancements
Leadership Perspectives
“Next-Gen SIEM was an iteration. AI-Gen is a fundamental architectural reset,” said Colby DeRodeff, Co-Founder and CEO of Abstract.
“AI isn’t a feature bolted onto a legacy platform. It must be embedded across the data pipeline from ingestion to detection to investigation. We built Abstract as AI-Gen from day one. The market validated that vision with 380% ARR growth last year. Now we’re formalizing what customers already know: composable, AI-native security operations are the future.”
Matt Bigge, Partner at Crosslink Capital, added: “As a day-one investor, I saw early that Abstract wasn’t trying to compete in the legacy SIEM category. They’re building the platform to redefine it. This launch marks an important milestone in what I believe will be a generational shift in how enterprises approach security data and detection.”
Marco Maiurano, Chief Information Security Officer at Mizuho and Advisor to Abstract, also commented: “Security leaders in highly regulated environments cannot afford architectural constraints. As data volumes expand and workload per analyst increases, platforms must deliver both adaptability and governed AI assistance at scale. A composable, streaming-first model represents a necessary evolution for modern security operations.”
Driving Impact from “Signal to Scale”
Entering 2026 under the theme Signal to Scale, Abstract is focused on accelerating adoption of the AI-Gen model across enterprise and regulated markets. Security leaders increasingly view data strategy as the foundation of effective AI-powered security operations. By shifting analytics left into the data stream and embedding AI in core workflows, Abstract reports:
- 65–75% reduction in SIEM-related costs
- Faster mean time to detect (MTTD)
- Faster mean time to respond (MTTR)
“Security teams have outgrown legacy SIEM platforms,” said Richard Stiennon, Chief Research Analyst at IT-Harvest.
“Next-gen SIEMs that leverage AI represent a new architecture purpose-built for today’s cloud-native, high-velocity environments.”
Errol Weiss, Chief Security Officer at Health-ISAC, echoed this vision:
“What stands out about Abstract is not just the performance, but the flexibility. AI-Gen Composable SIEM gives security teams architectural control while accelerating detection and reducing operational friction. That’s a rare combination.”
