Webinar

BIX: AI That Thinks Like a CISO

BIX isn’t just AI. It’s cyber risk intelligence – built from the ground up to think like a CISO.

Watch Gaurav Banga, CEO of Balbix, and Vinay Sridhara, CTO of Balbix, for a behind-the-scenes look at how BIX was engineered to help security leaders make smarter, faster decisions – especially when the pressure is on and the budget isn’t budging.

In this session, you’ll discover:

How BIX connects the dots across vulnerabilities, assets, threats, and business context
Why transparency and explainability aren’t optional – they’re critical for trust and action
The key questions every CISO should ask before buying into “AI-powered” platforms
How BIX helps you move from visibility to action with confidence

If you’ve ever wondered what real AI looks like under the hood – not just in slide decks – this is the deep dive you’ve been waiting for.

What is this webinar about?: This webinar offers an exclusive look at BIX: AI That Thinks Like a CISO — Balbix’s AI-powered cyber risk intelligence platform. You’ll learn how BIX is engineered to help security leaders make smarter, faster, and more defensible decisions under pressure.
What will I learn from this webinar?: You’ll discover:

How BIX connects vulnerabilities, assets, threats, and business context

Why transparency and explainability are critical for AI-driven decisions

How to spot AI-washing and properly evaluate “AI-powered” cybersecurity tools

How BIX empowers security teams to move from visibility to action with confidence
What makes BIX different from other AI cybersecurity tools?: BIX is built to think like a CISO — not like a chatbot or a generic AI model. It delivers explainable, actionable intelligence that directly connects technical risk to business impact, without the black-box mystery common in many AI solutions.
What should I look for in “AI-powered” cybersecurity platforms?: The webinar will walk through essential questions every security leader should ask, including:

Does the AI offer explainable, defensible outputs?

Can it connect technical findings to business context?

Is it truly supporting decision-making, or just automating existing tasks?

How can you spot AI-washing in the tools you’re evaluating?