AI Security Platform for Mobile Apps, LLMs & Agentic AI in BFSI

AI security refers to the set of practices, tools, and frameworks designed to protect AI systems—including machine learning models, large language models (LLMs), and agentic AI—from adversarial attacks, data poisoning, model theft, and runtime exploitation. In the BFSI context, AI security also encompasses protecting AI-driven fraud detection, credit scoring, and customer service systems from manipulation or compromise by malicious actors.

Protectt.ai's AppProtectt platform uses Runtime Application Self-Protection (RASP) with 100+ deep-tech security features to protect mobile banking and fintech apps in real time. It defends against runtime hooking, reverse engineering, app spoofing, SMS attacks, MITM attacks, and compromised device risks—with zero performance overhead and zero trust architecture, ensuring secure access whether users are inside or outside organizational networks.

LLM runtime security deploys an intelligent firewall that monitors and filters interactions with large language models in real time, blocking adversarial prompt injections, data extraction attempts, and model manipulation. BFSI organizations deploying AI chatbots, automated advisory tools, or LLM-powered workflows need this layer to prevent financial fraud, sensitive data leakage, and regulatory non-compliance arising from AI system exploitation.

AI red teaming is the process of simulating adversarial attacks specifically against AI systems—including LLMs, ML models, and agentic AI pipelines—using automated and manual techniques to uncover vulnerabilities unique to AI, such as prompt injection, model inversion, and reward hacking. Unlike traditional penetration testing focused on network and application layers, AI red teaming evaluates the security posture of AI components themselves, which have entirely different attack surfaces.

Protectt.ai's platform is purpose-built to support compliance with RBI Master Directions on Cyber Resilience and Digital Payment Security Controls, SEBI's Cybersecurity and Cyber Resilience Framework, and NPCI SIM and Device Binding controls. It automates policy enforcement, generates audit-ready reports, and provides continuous monitoring—reducing manual compliance work by up to 80% and audit preparation time by up to 90% for banks, NBFCs, and capital market intermediaries.

An Agentic AI Lifecycle Protection platform secures autonomous AI agents—systems capable of making independent decisions and taking actions—throughout their entire lifecycle, from development and training to deployment and production. Protectt.ai's platform covers ML model scanning for supply chain integrity, LLM runtime firewalling, and AI red teaming, providing comprehensive coverage against threats unique to self-directed AI systems used in BFSI operations.

No. Protectt.ai is engineered for zero performance overhead, meaning its security capabilities run in the background without degrading app speed, responsiveness, or user experience. The lightweight SDK integrates seamlessly into Android and iOS applications, and features like Silent Mobile Verification eliminate friction by verifying identity via carrier networks without requiring OTP inputs from end users.

Protectt.ai holds ISO 42001 (AI Management System), ISO 27001 (Information Security Management), ISO 22301 (Business Continuity), and PCI DSS (Payment Card Industry Data Security Standard) certifications. The company has also been recognized as Cybersecurity Company of the Year 2023, Best Enterprise Security 2023, and Banking Security Solution 2023, and holds a Gartner Peer Insights rating of 4.9 out of 5.