Agentic App for real-time AI security management

Client

Operating at the intersection of cybersecurity and AI, a US-based startup addressing the critical security gaps introduced by the rapid adoption of Large Language Models (LLMs).

Challenge

The product required building an AI system capable of monitoring and policing other AIs in real time
Threat actors were beginning to target AI models directly through prompt injection, model poisoning, and malicious agent workflows
Existing security tools could secure the perimeter while remaining blind to AI-layer data exfiltration risks.

Solution

4-week AI-first Sprint Zero de-risked MVP scope, threat models, and architecture before development
Compliance controls embedded into workflows to minimize friction
CISO-grade command center translating detection signals into clear enterprise risk posture reports
Java + Python ML detection engine identified prompt injection, poisoning, and malicious agents
Java, React, Python, Mongo DB, AWS Bedrock

Impact

Delivered a prototype in 6 weeks and a first-to-market AI security platform in 12 weeks
Covered 22,000 agentic user flows across the platform
Reduced compliance review time by 40% for enterprise design partners
Achieved 50% faster detection-to-remediation cycles, the metric CISOs use to justify security investments
Secured $2M+ in seed funding on the back of the MVP, validating both the product and the market

Strategic Significance

Demonstrates Indexnine’s ability to turn emerging AI security risks into a real-time CISO command center, combining speed, technical depth, and enterprise-grade UX to simplify management of complex risk signals.

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