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Quantum Light Secures $1.1M Extension, Totaling $2.1M

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July 6, 2026 by Ivy Delaney

Quantum Light has secured $1.1 million in a pre-seed extension, bringing the total funding for its novel materials work to $2.1 million USD and signaling strong investor confidence in its approach to color technology. Backed by Venrex and I2BF Global Ventures, the company is focused on developing quantum pigments for applications requiring precise light control. “Quantum Light commands how light behaves rather than simply reflecting it,” explains I2BF Global Ventures Managing Partner Mike Lousteau, highlighting the core differentiation of this technology. The new capital will accelerate sampling, testing, and development as Quantum Light aims to integrate its advanced color engineering into real-world materials like coatings, plastics, and textiles.

Quantum Light Secures $2.1 Million USD in Pre-Seed Funding

Quantum Light has now secured a total of $2.1 million USD in pre-seed funding, bolstered by a recent $1.1 million extension that demonstrates sustained investor enthusiasm for its novel approach to material science and color engineering. This latest round included participation from Venrex and I2BF Global Ventures, joining existing angel investors in backing the company’s development of quantum dot pigment technology; the influx of capital signals confidence beyond the initial investment and positions Quantum Light to capitalize on growing demand. The company intends to utilize these funds to accelerate sampling, testing, and validation of its technology across a diverse range of applications, from coatings and plastics to textiles.

The core of Quantum Light’s innovation lies in its ability to manipulate light itself, a departure from traditional pigment technology that merely reflects it. Investor Amsal Madhani notes, “Quantum Light is doing what the best technology companies do: they are solving a problem that seemed impossible, building with conviction towards that goal, and also making our world more beautiful.” This capability stems from the use of quantum dots, nanocrystals that emit light at specific wavelengths with exceptional purity, allowing for greater control over color and light interaction.

Mike Lousteau, Managing Partner of I2BF Global Ventures, further emphasized this distinction, stating, “Most materials companies refine what exists.” Olga Alexopoulou, CEO of Quantum Light, stated, “This pre-seed extension gives us the ability to move faster.” The company is actively expanding its capacity to serve commercial partners and scale its platform for broader implementation across materials-led industries, aiming to establish a new category of pigment technology that actively engineers light interaction rather than simply adding color.

Most materials companies refine what exists. Quantum Light commands how light behaves rather than simply reflecting it.

Mike Lousteau, Managing Partner of I2BF Global Ventures

The pursuit of more vibrant and controllable color has historically relied on refining existing pigment technology; however, Quantum Light is taking a different approach through the manipulation of light itself at the quantum level. The company has secured a total of $2.1 million USD in funding, including a recent $1.1 million.

At Quantum Light, our mission is to bring advanced colour engineering into real-world materials, colours, pigments and design applications. This pre-seed extension gives us the ability to move faster. We are building a new category of pigment technology, one that does not simply add colour, but engineers how materials interact with light.

Olga Alexopoulou, CEO of Quantum Light
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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