Classiq announced a new AI agent layer designed to transform natural language intent into structured, executable quantum applications. Powered by the first generation of expert-level quantum agents, this capability allows users to go beyond manual gate-level coding by writing high-level computational goals in plain language. Unlike traditional large-scale language model (LLM) code assistants, Classiq Quantum Agent runs directly on the company’s model-based platform, ensuring that the generated programs are optimized, verified, and ready to run on real quantum hardware.
Agent workflows are designed to support the entire quantum development lifecycle, from translating domain-specific problems into quantum models to optimizing circuits for specific hardware constraints. This “hardware agnostic” approach keeps applications compatible with evolving quantum systems. Classiq’s primary goal is to move quantum development from one-off experiments to repeatable, enterprise-grade “knowledge assets” that can be maintained and expanded as the technology matures.
Expert quantum agents: functions and domains
Classiq Quantum Agent acts as a trained development partner specializing in several high-value sectors.
- Pharmaceutical and chemical: Translate molecular modeling and drug discovery problems into scalable quantum algorithms.
- finance: Automate circuit design for risk analysis, portfolio optimization, and Monte Carlo simulation.
- Aerospace and automotive: Optimize structural analysis and logistics workflows under real-world constraints.
- Quantum error correction: Helps implement complex error correction protocols for next-generation systems.
Model-based abstraction and validation
A key differentiator of the Classiq platform is its synthesis and optimization engine. When a user provides a natural language prompt, the agent generates a functional model rather than raw code. This model is automatically synthesized into an optimized quantum circuit. This results in output like this:
- Structured and maintainable: It’s easy for teams to iterate and integrate with existing DevOps pipelines.
- Fully compilable: It is guaranteed to meet the logical and physical requirements of the target quantum processor.
- Optimized for hardware: Automatically adjusts to qubit connectivity, gate set, and coherence time.
For the official press release about Classiq’s Quantum AI agent, see Classiq’s announcement here. Additional technical context for the company’s model-based synthesis technology can be found on the Classiq Quantum AI page here.
April 23, 2026
