Research Agents
Read papers, propose experiments, generate notebooks, and maintain persistent context across quantum programs.
AI quantum intelligence systems
One orchestration layer.Every compute path.Quantum ready.
EvaQuantum, the quantum division of Eva Live Inc., builds AI systems for quantum research, autonomous quantum software engineering, hybrid AI + HPC optimization, and next-generation compute scheduling.
Strategic focus
AI software first, quantum hardware partnerships as the ecosystem matures.
EvaQuantum focuses on the software and intelligence layer instead of fabrication facilities: research agents, quantum developer tools, circuit optimization, compiler intelligence, control software, and heterogeneous compute orchestration.
QuantumOS dashboard
A command center for research programs, simulator fleets, hybrid jobs, and quantum provider routing.
Hybrid workload
GPU simulation active
Quantum route under review
Quantum DevOps
Generate, test, benchmark, and migrate quantum code across Qiskit, Cirq, PennyLane, CUDA-Q, and custom stacks.
Hybrid Optimizer
Combine neural heuristics, GPUs, HPC simulation, approximate solvers, and quantum routines when useful.
Provider Routing
Prepare workloads for placement across classical infrastructure, accelerators, and future quantum hardware providers.
Quantum AI
From research questions to working quantum software.
EvaQuantum builds domain-specific AI systems that help teams move from paper, hypothesis, or optimization goal into executable experiments, simulation workflows, and production-ready quantum software.
The goal is practical value now: better code, faster simulation, smarter optimization, and a clean path toward quantum hardware as it becomes commercially useful.
01
Algorithm discovery
Explore candidate quantum routines and compare them against classical and approximate approaches.
02
Circuit optimization
Refactor circuits for depth, noise, device constraints, cost, and hardware-specific performance.
03
Compiler intelligence
Build AI-assisted compiler and control workflows for noisy and emerging hardware platforms.
Intelligent scheduler
An AI that learns when a problem should run classically, approximately, or quantum.
EvaQuantum's long-term thesis is an adaptive memory system that composes workflows automatically: choosing CPU, GPU, NPU, HPC, or quantum paths based on cost, accuracy, availability, and learned outcomes.
Roadmap
Designed to create value before fault-tolerant quantum computers are widely available.
Phase 1
Build a domain-specific AI platform for quantum research and software engineering, with autonomous code generation and GPU-based hybrid optimization.
Phase 2
Expand into AI-driven quantum circuit optimization, compiler technology, and quantum control software through hardware vendor partnerships.
Phase 3
Become the orchestration layer across CPUs, GPUs, NPUs, and quantum processors, with automated calibration and workload placement.
Strategic Layer
Use external memory and adaptive AI to learn which computational path works best for each class of problem.
Partnership strategy
Partner with hardware vendors, research teams, and enterprises building quantum advantage.
EvaQuantum is positioned to collaborate with quantum hardware providers, HPC teams, pharma and chemistry groups, finance and logistics organizations, and enterprises that need an AI layer for next-generation compute.
Potential partners
Built for teams that need intelligent compute decisions and quantum-ready software.
Quantum hardware vendors
HPC and cloud providers
Pharma research teams
Materials science labs
Financial optimization groups
Enterprise AI teams
Partnerships
Start a quantum intelligence conversation.
For quantum software, research AI, hybrid optimization, hardware partnerships, and strategic investment opportunities, contact the EvaQuantum team to discuss pilots and product direction.