SentinelFlow

Security teams receive thousands of alerts every day, but investigating each one still requires analysts to manually collect evidence, switch between tools, validate findings, and prepare reports. This process is slow, repetitive, and often leads to inconsistent decisions. SentinelFlow was built to solve that problem using collaborative AI agents instead of a single AI assistant. When an alert is received, SentinelFlow launches a coordinated investigation where six specialized AI agents work together through Band. Each agent has a dedicated responsibility, including triage, threat hunting, validation, risk assessment, red-team challenge, and incident coordination. Rather than working independently, every agent shares evidence, challenges assumptions, and contributes to a common investigation workspace. As the investigation progresses, SentinelFlow continuously builds a live knowledge graph that connects entities, evidence, relationships, attack patterns, and business impact. Every decision remains transparent and explainable, allowing analysts to understand how conclusions were reached. Once the investigation is complete, SentinelFlow automatically generates an executive-ready investigation report containing findings, supporting evidence, risk assessment, timeline, and recommended actions. Every investigation is also stored with a complete audit trail that can be replayed for future review. Our goal is not to replace security analysts but to augment them with a collaborative AI workforce that reduces investigation time, improves consistency, and helps security teams make faster, evidence-backed decisions.