Artificial Intelligence, Quantum Software

Bloq Quantum launches Maya, an AI agent for quantum teams

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October 27, 2026 by Ivy Delaney

Bloq Quantum has launched Bloq Maya, an AI agent designed to accelerate quantum computing development for businesses. The platform provides access to over 15 pre-built, research-grade algorithms, including QKAN, PQK, QEMCMC and QSVM, lowering the barrier to entry for complex quantum applications. “Translating complex quantum workflows into production-ready enterprise applications remains a significant bottleneck for enterprises,” said Sreekuttan L S, Co-Founder and CEO of Bloq Quantum. Bloq Maya is designed to accelerate quantum use case development by a factor of 10, addressing a key challenge in translating theory into enterprise solutions.

Bloq Maya: AI Agent for Enterprise Quantum Workflow

Bloq Maya’s Visual Circuit Studio enables users to construct parameterized quantum circuits without requiring extensive coding experience, which significantly alters the typical development process. This intuitive interface allows for the design of complex quantum workflows through a visual builder, eliminating the need for deep expertise in quantum programming languages. The platform’s hardware-agnostic execution capability further streamlines development by allowing code written within Bloq Maya to run smoothly across cloud simulators and physical quantum processing units from providers like IBM and AWS Braket.

By automating infrastructure management and reducing coding dependencies, Bloq Maya aims to reduce the time and manpower traditionally required for quantum solution development by half. This efficiency is intended to enable businesses in sectors like finance, automotive and pharmaceuticals to explore impactful applications, including risk modeling, portfolio optimization and complex simulations, positioning the agent as a tool to unlock quantum computing’s potential for a wider range of organizations and use cases.

Bloq Maya removes the friction so teams can go from an idea to a tested quantum use case up to 10x faster.

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Avatar of Ivy Delaney

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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