Making Security as Fast as the Threat
Enterprise security teams are fighting machine-speed attacks with human-speed tools — and losing. We built Quellra to change that. GPU-native from day one. Autonomous by design.
Our Mission
Make enterprise security teams as fast as the threats they face. No sampling. No delays. No analyst bottleneck. GPU-native intelligence that detects in 0.4ms, investigates in 500ms, and contains in seconds.
What We Believe
GPU-Native Thinking
We don't bolt GPUs onto CPU architectures. We build from accelerated compute up — every pipeline stage designed for parallelism.
Zero Compromise Detection
100% telemetry coverage. No sampling, no shortcuts. Attackers cannot hide in the events you chose not to analyze.
Autonomous by Design
AI agents that act, not just alert. Pre-approved containment at machine speed. Analysts freed for strategy, not triage.
Physical Security Matters
OT/ICS environments deserve the same AI-native protection as IT. Jetson Edge brings GPU inference to the factory floor.
Built by Engineers Who Think in CUDA
Security researchers, ML engineers, and GPU systems builders united by a single conviction: enterprise security must operate at machine speed.
Moez Nasir
Co-Founder & CTO
Computer Engineering, FAST NUCES. Research background in AI-based defect detection systems. Expertise in embedded systems, machine learning, and full-stack development. Leading Quellra's CUDA kernel engineering and Morpheus pipeline architecture.
Fatima Irshad
Co-Founder & Head of AI
Software Engineering graduate specializing in Computer Vision and Machine Learning. Huawei Cloud Certified (AI). Experience building production vision systems at Arch Technologies. Leading Quellra's TensorRT model optimization and NeMo fine-tuning pipelines.
Muhammad Haris
Co-Founder & ML Engineer
AI/ML Engineer with mathematics foundation. Google Cloud ML Engineer certified. IBM AI Developer specialized. Building Quellra's threat detection models, RAPIDS analytics pipelines, and NeMo behavioral baselines.
Our Journey
Team formed. Core research on GPU-accelerated threat detection begins.
Quellra concept validated. NVIDIA Morpheus pipeline architecture designed.
$2M seed round closed from ZaynVC. Full-time development begins.
Morpheus pipeline prototype. First design partner conversations.
First enterprise pilot deployments targeted.
Built on the Full NVIDIA AI Stack
Quellra uses 10+ NVIDIA technologies across every product layer: Morpheus for detection, TensorRT for inference, NeMo for model training, NIM for agent serving, RAPIDS for analytics, Triton for multi-model deployment, Jetson Orin for edge, and DGX H100 for foundation model training.
What We're Building
A GPU-native security AI platform with five specialized products sharing a single telemetry lake, Morpheus pipeline, and NeMo/NIM serving layer. Quellra Core for real-time detection, Phantex for adversarial red teams, Vexid for identity defense, Vendex for supply chain, Huntix for threat hunting, and Simara for OT digital twin simulation. One CISO buyer. One ecosystem.
Join the Team
We're looking for CUDA engineers, ML researchers, security architects, and enterprise sales leaders who want to define GPU-native cybersecurity. Remote-first. Early-stage equity.
Let'sBuildtheFutureofSecurityTogether
Whether you're a Fortune 500 CISO evaluating GPU-native detection, an investor interested in the cybersecurity AI space, or an engineer who thinks in CUDA kernels — we'd love to talk.