Anti-cheat for
AI Models
As inference moves to the edge, your model IP becomes vulnerable.
fortif.ai detects, blocks, and proves unauthorized access to weights and activations at runtime.
The Edge Inference Dilemma
AI inference is moving to customer-owned infrastructure and edge devices to reduce latency and costs. But once your model leaves your secure cloud, it’s exposed.
Hostile Environments
Models deployed on customer on-prem servers or edge devices run on hardware you don't control. Root access means total visibility for them.
Memory Dumping
Attackers can dump GPU memory to extract weights, biases, and activations, effectively stealing your IP for fine-tuning or replication.
Silent Extraction
Traditional API security (WAFs) cannot see what happens inside the GPU memory space. Theft happens silently without network logs.
Runtime Integrity for AI
fortif.ai operates at the system level, sitting between the OS and the ML runtime. We instrument the execution environment to monitor memory access patterns in real-time.
Zero-Latency Overhead
Optimized for high-throughput inference. Our lightweight agents impose negligible performance penalty on GPU operations.
Obfuscation Resilient
Unlike static encryption that must be decrypted for inference, fortif.ai protects the model during execution when it is most vulnerable.
Total Lifecycle Protection
From detection to enforcement, fortif.ai provides the tools you need to secure your intellectual property.
Detect
Identify unauthorized attempts to inspect, probe, or dump model memory and execution state in real-time.
Block
Actively prevent live extraction of model weights, biases, and activations on compromised customer systems.
Prove
Generate cryptographically signed, audit-grade forensic evidence of abuse for legal and compliance enforcement.
Trusted By Teams In
About the Founders
Building the security layer for the AI era.
Atman Kar
Co-founder
Atman is a systems and hardware engineer focused on building secure, high-performance compute platforms. He studied engineering at Birla Institute of Technology and Science (BITS), Goa, with a strong foundation in computer architecture and signal processing. At fortif.ai, Atman leads the technical direction around runtime protection of AI models, bringing a deep understanding of how memory, accelerators, and low-level systems are actually attacked in real deployments.
Sayan Mitra
Co-founder
Sayan is a graduate of IIT Madras in Electrical Engineering with a focus on Computer Architecture, and has worked as an AI Engineer specializing in AI systems and low-level execution. His expertise spans performance-critical AI infrastructure, runtime behavior, and execution close to the hardware. At fortif.ai, Sayan leads the development of secure AI runtimes, enforcing control over model execution, and creating system-level mechanisms to protect AI intellectual property without compromising performance.