All Articles
Filter by Category
From Planning to After-Action: The Full Reporting Lifecycle of Major Events
Event security reporting doesn't begin when the gates open — it starts weeks earlier with threat assessments and venue profiling, and it doesn't end until the after-action review is filed. This piece follows Celeste, a hypothetical senior event security analyst preparing for a 200,000-person music festival, through all four stages of the reporting lifecycle: pre-event threat assessment, operational daily SITREPs, real-time incident reports, and post-event after-action review.
The Digital Battlefield: Cyber and Physical Threats Converging at Major Events
When a cyberattack hits a major event, the consequences rarely stay contained to IT systems — they show up at the gates, in the crowd, and on the stadium floor within minutes. This piece follows Crystal, an event security analyst managing a major sporting event, through three scenarios where digital incidents cascade directly into physical emergencies: a ticketing system breach, a compromised venue app, and a coordinated deepfake and drone threat. Each scenario illustrates the same underlying problem: most event security teams are still running separate workflows for cyber and physical threats, which means when the two converge, nobody has the full picture.
3 Finance Intelligence Reports Watchfloor Analysts Can Deliver in Record Time Using Indago
Watchfloor analysts in finance and market intelligence face a pressure most roles don't: leadership needs answers before the market reacts, and the window between a breaking event and an executive briefing is often measured in minutes.
This piece walks through the three reports that define success in this role, the specific workflow challenges each one creates, how the best analysts are producing these accurately and under pressure — and what the right tooling actually makes possible.
Why Human-in-the-Loop AI Is Essential for Intelligence and Security Operations
As AI adoption accelerates across intelligence and security operations, many organizations measure success by how many humans they remove from the workflow. In high-stakes environments, that approach creates serious risk. Yet this framework fundamentally misunderstands productivity in intelligence environments, where the cost of error far exceeds the cost of human oversight.
AI-Driven OSINT Summarization: How Analysts Turn Open-Source Collection into Intelligence Deliverables
The most common misconception about AI-driven OSINT summarization is that it's about automating analysis. It's not. The real value lies in automating the mechanical work that prevents analysts from doing analysis in the first place. The future of OSINT is about machines doing the preparation so that humans can think better, faster, and with greater confidence in high-stakes environments.