Co-founder & CEO
Profile summary: nodeQ • Quantum Network Engineer | Cybersecurity Lead · PhD at Politecnico di Torino
Helix 42
Helix 42 provides a unified orchestration platform that integrates classical, AI, and quantum compute resources via a single control plane built on Kubernetes and Slurm. Its agentic AI engine dynamically schedules workloads, abstracts device‑specific APIs, and enforces zero‑trust security, enabling enterprises and research teams to run hybrid workloads without specialized quantum expertise.
Updated 4 months ago
Funding
Funding rounds are not available yet.
Founders
Product
Problem
Organizations that need to run workloads across classical, AI, and emerging quantum hardware face fragmented tooling, complex scheduling, and high expertise requirements. Inefficient resource allocation and the need to understand device‑specific APIs increase operational costs and limit the portability of quantum applications.
Solution
Helix 42 delivers an orchestration platform that unifies classical, AI, and quantum compute resources under a single control plane. The system employs an agentic AI stack to monitor workload demands and automatically allocate resources, adjusting schedules in real time. By building on Kubernetes and Slurm, the platform integrates with existing data‑center and cloud environments while providing quantum‑native extensions for emerging hardware. Security‑by‑design principles, including zero‑trust networking and confidential computing, protect data across heterogeneous nodes. The platform abstracts device‑specific details, allowing users to submit workloads without deep knowledge of each quantum device, thereby improving portability and reducing the need for specialized staff.
Target Audience
Helix 42 targets enterprises, research institutions, and cloud providers that operate mixed compute environments and need to incorporate quantum processing into production workloads. The primary customers are teams responsible for high‑performance computing, AI model serving, and emerging quantum applications.
Features
- Agentic AI core that continuously diagnoses resource bottlenecks and rebalances workloads across classical, AI, and quantum nodes
- Dynamic resource allocation and workload scheduling driven by real‑time telemetry
- Hybrid orchestration layer built on Kubernetes for containerized workloads and Slurm for HPC/quantum job management
- Quantum‑native architecture that exposes a unified API for multiple quantum hardware providers
- Security‑by‑design implementation with zero‑trust access controls and support for confidential computing enclaves
- Portable abstraction layer that hides device‑specific APIs, enabling workload portability across different quantum processors
- Integrated AI model deployment tools for inference pipelines that run on both classical and quantum accelerators