Delft University of Technology (TU Delft) deep-tech spin-off MagiQware has finalized its pre-seed funding round, reaching a total of €575,000 ($658K USD) in investment capital. Initially launching with a €500K close led by early-stage investment manager LUMO Labs via the TTT.AI programme, the round was expanded to €575K following a subsequent co-investment completion by Graduate Ventures and Delft Enterprises B.V. The capital injection is allocated to accelerate product development, validate automated software compilers, and expand the technical engineering team.

                         [ MagiQware Capitalization Matrix ]
  Funding Stage       ──► Pre-Seed Round extended to €575,000 (Expanded from initial €500K close).
  Sovereign Investors ──► LUMO Labs (Lead), Graduate Ventures, and Delft Enterprises B.V.
  Algorithmic Target  ──► Reinforcement learning models to reduce magic state factory circuit overhead.

The startup addresses the steep physical resource overhead required to maintain fault-tolerant quantum computing (FTQC). While standard quantum algorithms rely on quantum error correction to shield operations from phase decoherence, executing non-Clifford logical gates requires specialized algorithmic subroutines known as magic state factories. These factories filter out physical noise to distill high-fidelity “magic states,” but the distillation process acts as a massive bottleneck, frequently consuming up to 90% of a full-stack quantum computer’s physical qubit and circuit footprint.

MagiQware constructs specialized optimization tools within the quantum compilation and software stack to lower these entry barriers. Led by CEO Arash Ahmadi, PhD and CTO Shakeeb Majid, alongside Head of Device Sahar Hejazi (PhD) and Head of Theory Ali Moghaddam, PhD, the technical unit deploys specialized reinforcement learning models to orchestrate magic state production. By using automated AI agents to dynamically discover and optimize distillation circuit architectures, MagiQware’s compilers have demonstrated up to a 40% reduction in circuit length for target factories, dropping the aggregate hardware overhead needed by full-stack system developers without modifying the physical hardware layer.

The official venture capital transaction metrics and funding parameter briefs can be reviewed through LUMO Labs here. The expanded investment data and technical team allocations can be audited via the Graduate Ventures Corporate Update here, while the early optimization milestones and commercial roadmap timelines are accessible on the MagiQware Institutional Disclosure here.

July 6, 2026

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