Terra Quantum has announced the closed beta launch of TQ42 Studio, a quantum AI development environment that includes two components: QAI Hub, a no-code quantum machine learning platform, and Qode Engine, a Python SDK for advanced users. The goal of the platform is to lower the barrier to entry for quantum machine learning by offering visual model-building tools and automating quantum component integration. The announcement coincides with World Quantum Day 2025 and invites users to request early access to participate in the testing phase.
QAI Hub enables users to design and test hybrid quantum-classical models through a graphical interface. At its core is TQ Copilot, an agentic AI assistant that performs tasks such as tuning quantum layers or adjusting hyperparameters based on natural language input. The platform currently uses classical HPC infrastructure (CPUs, GPUs), while support for select QPUs is under development. QAI Hub is intended to assist data scientists and machine learning engineers in rapidly prototyping quantum workflows without requiring quantum programming expertise.
The platform emphasizes several technical advantages of quantum AI, including improved model generalization, enhanced data encoding, and the ability to extract insights from smaller datasets. It is designed to support use cases such as industrial forecasting, optimization, and anomaly detection. Through visual design and AI-guided automation, QAI Hub enables experimentation with hybrid quantum architectures while maintaining a focus on real-world application performance.
For users requiring code-level control, Qode Engine offers direct access to quantum libraries including TQml, TetraOpt, TQoptimaX, and QuEnc. It also supports integration with CI/CD workflows and scalable backend orchestration. While QAI Hub serves as an accessible entry point, Qode Engine is targeted toward developers building production-ready systems with advanced optimization requirements.
Participants in the closed beta will receive access to both QAI Hub and Qode Engine, along with trial compute credits. Feedback collected during the beta will be used to refine the platform’s features, including the TQ Copilot, infrastructure flexibility, and deployment options. Interested users can request access by completing a brief application form and outlining their quantum AI use cases.
Read the full announcement from Terra Quantum here.
April 15, 2025
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