Kipu Quantum brings quantum-enhanced machine learning to IBM Quantum Functions Catalog with Rimay
New Function gives IBM Quantum Flex and Premium Plan users direct access to Kipu Quantum's feature extraction technology for improving existing machine learning workflows
Berlin / Chicago, 12 November 2026 – Kipu Quantum today announced that Rimay, its quantum feature extraction technology for machine learning, will be available through IBM Quantum Functions Catalog, giving IBM Quantum Flex and Premium Plan users a direct way to apply Kipu’s quantum machine learning capabilities within the IBM Quantum Platform.
The launch extends Kipu Quantum’s presence on the IBM Quantum Platform, from optimization into quantum machine learning. Kipu’s Iskay Quantum Optimizer is already available in the IBM Quantum Functions Catalog. Users can submit classical optimization problems and execute Kipu’s compressed quantum algorithms on IBM quantum computers.
Rimay addresses a different challenge: improving the information available to machine learning models. Rather than replacing an organisation’s existing model or ML stack, Rimay adds a quantum feature extraction step. Classical data is processed using quantum feature extraction to identify additional features and correlations before the enriched data is returned to conventional machine learning models.
Rimay is designed for data science teams working with tabular datasets where prediction quality has plateaued. It slots into existing machine learning pipelines as a drop-in automated feature extraction algorithm. It encodes training data into a Hamiltonian, which then maps each feature to a qubit, and runs a counterdiabatic evolution on IBM’s quantum computers to generate quantum-transformed features.
Users can then feed the quantum-transformed features into their existing classical models, either on their own or alongside the original features.
In one recent deployment with a Fortune 100 company, Rimay was used to enhance an existing customer-intent prediction model using tabular data on the latest IBM Quantum Nighthawk processor. The quantum-enhanced workflow improved prediction performance while integrating with the customer’s existing classical machine learning stack, with the potential to deliver significant operational savings.
Alongside the launch of Rimay’s availability in the IBM Quantum Functions Catalog, users will have access to a credit-risk classification tutorial, included in IBM Quantum documentation, which will show how to prepare tabular data, fit a quantum feature map on IBM quantum computers, and use the resulting features within a conventional machine learning workflow.
“Putting Rimay directly into the IBM Quantum Functions Catalog is an important step in making quantum machine learning easier to use. Companies should not have to rebuild their machine learning stack or become quantum experts to find out whether quantum computing can improve a real business problem. With Rimay, the models stay unchanged, the stack stays unchanged, but the data becomes richer. For AI teams, that means improving what existing models can learn from the same underlying data, rather than simply adding more compute or complexity. Making that capability available as a function through the IBM Quantum Platform gives teams a straightforward way to test where quantum feature extraction creates measurable additional value.”
Dr. Tobias Grab, Managing Director of Kipu Quantum
“We appreciate the progress Kipu Quantum is making to bring quantum computing into practical machine learning workflows. The addition of Rimay to the IBM Quantum Functions Catalog gives data scientists an accessible way to explore quantum feature extraction that complements existing classical models — and helps them investigate new correlations in their data, and move toward solving real business challenges of value.”
Scott Crowder, Vice President, IBM Quantum Adoption and Business Development
About Rimay
Rimay is Kipu Quantum’s quantum feature extraction service for machine learning. It transforms classical data into quantum-derived features designed to complement existing machine learning models. Rimay can process tabular data as well as representations derived from image and time-series data and has been demonstrated on IBM Quantum hardware.
About Kipu Quantum
Kipu Quantum is a quantum software company focused on delivering real business impact with quantum computing today. The company develops application- and hardware-specific quantum algorithms and hybrid quantum-classical products that turn today’s commercial quantum hardware into deployable tools for real enterprise challenges, particularly in optimization and machine learning. Kipu’s quantum software has already outperformed established classical approaches using real quantum processors. Through the Kipu Quantum Hub, hundreds of organizations access quantum computing tools and leading quantum hardware. Kipu is backed by leading deep-tech investors including HV Capital, the DeepTech & Climate Fonds, Quantonation, Verve Ventures and AQAL Group, and works across an ecosystem that includes IBM Quantum, NVIDIA, IonQ, QuEra and Pasqal. Led by Tobias Grab, Kipu Quantum is headquartered in Berlin and has a presence in Karlsruhe, UK, Spain, Italy and France.