Exaforce has developed an agentic SOC platform that supports the full security operations lifecycle through autonomous AI agents called Exabots. These handle detection, triage, investigation, and response for cloud and SaaS environments. The platform ingests and unifies high-volume telemetry into a correlated data view, powering real-time analysis without reliance on traditional SIEM rules or manual query languages.
Unlocking the power of agents requires memory. Just like human memory, a good agentic memory organizes knowledge. It helps agents retrieve the right knowledge based on context and learn to make smarter decisions and take optimized actions over time.
"In agentic environments, agents mutate state across data, systems, and configurations in ways that compound fast and are hard to trace," says Pranay Ahlawat, Chief Technology and AI Officer at Commvault.
Agentic AI systems are designed to interpret user requests, select the appropriate models or tools, evaluate intermediate outputs, and refine their decisions over multiple steps. This iterative reasoning loop enhances the segmentation process significantly.
A key element of the project is discovering fundamentally new ways of working: Research that results only in incremental improvements in existing methods and models that already exist is specifically excluded from MATHBAC funding.
