Zapata Quantum and NVIDIA integrate agentic AI to automate quantum resource estimation. Zapata Quantum and NVIDIA have partnered to integrate agentic AI into quantum algorithm development by automating quantum resource estimation workflows. The collaboration focuses on streamlining a process used to determine the exact hardware specifications, error-correction budgets, and physical execution times required to run quantum applications. Initial engineering efforts are directed at complex quantum chemistry challenges, including pharmaceutical drug discovery, energy grid optimization, and advanced materials development, where benchmarking quantum algorithms has historically stood as a significant developer bottleneck. Conventional algorithm benchmarking and resource estimation typically require extensive multi-year efforts from domain experts spanning molecular modeling, software compilation, and hardware architecture evaluation. The joint workflow compresses this timeline by implementing an orchestrated multi-agent AI framework designed to automate these separate steps into a scalable system. The automated pipeline utilizes the NVIDIA Agent Toolkit software to establish tracking, observation, and operational guardrails for the underlying multi-agent AI setup, combining continuously verified software compilation layers with predictive models capable of calculating physical qubit counts and gate depths before a computation is initiated on live hardware backends. The cooperative methodology has been validated by testing its automated estimation protocols on homogeneous catalysis, building on Zapata's previous benchmarking datasets created during its participation across all technical segments of the DARPA Quantum Benchmarking program. Homogeneous catalysis presents a significant computational bottleneck for classical simulation, making it a critical test case for verifying how effectively the automated framework can identify high-value industrial workloads. To secure the intellectual property of this verification-aware automation approach, Zapata has also filed a provisional patent application detailing the implementation of its agentic framework for quantum computing applications. The official corporate disclosure detailing the technical collaboration, software workflows, and patent filings can be reviewed directly via the Zapata Quantum Investor Relations Portal here. June 23, 2026

Zapata Quantum teams with NVIDIA to apply agentic AI to accelerate quantum algorithm development. Insider Brief * Zapata Quantum is working with NVIDIA to apply agentic AI to automate quantum resource estimation workflows, initially targeting quantum chemistry applications in drug discovery, energy and advanced materials. * The collaboration is designed to reduce the expert time and cost required to benchmark quantum algorithms by combining AI orchestration, verified quantum workflows and feasibility models that estimate hardware needs before computation. * Zapata said the approach has been tested in homogeneous catalysis, building on its DARPA Quantum Benchmarking work, and the company has filed a provisional patent application for an "agentic framework for quantum." PRESS RELEASE - Zapata Quantum (OTCQB: ZPTA) ("Zapata" or the "Company") today announced it is applying agentic AI to accelerate quantum algorithm development by automating quantum resource estimation ("QRE") workflows, in collaboration with NVIDIA. The effort initially targets applications in quantum chemistry, including drug discovery, energy, and advanced materials development. "We believe that automation, powered by advances in AI and informed by domain-specific knowledge, is the key to scaling quantum application development for real-world applications such as drug discovery," said Yudong Cao, Zapata's Chief Technology Officer. "By working alongside NVIDIA, we're applying agentic AI to address the challenge of efficiently benchmarking quantum algorithms, an underappreciated bottleneck in quantum application development." Orchestrated Multi-Agentic AI Solution Today, the benchmarking of a single class of quantum algorithms often involves years of expert effort spanning molecular modeling, algorithm design, and hardware resource estimation. Zapata and NVIDIA are collaborating on an agentic AI workflow designed to compress this process into a scalable automated system to significantly lower the cost and time required. "Agentic AI is proving transformative in shortening the timeline to useful quantum applications," said Sam Stanwyck, Director of Quantum Product at NVIDIA. "This work with Zapata shows how crucial accelerated computing and AI is for practical and scalable quantum resource estimation, and how impactful that can be for developing meaningful applications in areas such as industrial quantum chemistry." The workflow combines AI orchestration, continuously verified quantum workflows, and an AI feasibility model capable of predicting hardware requirements before computation begins. The approach utilizes NVIDIA Agent Toolkit software to provide guardrails and monitoring for the workflow's initial multi-agentic setup. Approach Tested with Homogeneous Catalysis The initiative has already demonstrated the potential of the approach in the field of homogeneous catalysis, building on Zapata's prior work in the same area as part of the DARPA Quantum Benchmarking program. Homogeneous catalysis is a computationally demanding and strategically important quantum chemistry problem given its applicability to high-value areas such as pharmaceuticals, energy and advanced materials. The team of scientists from both companies now seeks to refine the methodology and broaden its application within quantum chemistry. Zapata also recently filed a provisional patent application related to an "agentic framework for quantum," reflecting the company's broader verification-aware AI approach to scalable quantum application development. "The future of quantum computing will not be determined solely by hardware progress but by our ability to systematically discover, evaluate, and develop high-value applications," said Cao. "AI has the potential to do for quantum application development what modern software tools have done for traditional software engineering - enabling researchers to move faster, explore more ideas, and focus their expertise where it creates the most value." Matt Swayne. With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]. Relevant. Matt Swayne May 12, 2026 Matt Swayne August 5, 2022 Matt Swayne October 23, 2020 Matt Swayne August 12, 2024 Mohib Ur Rehman January 23, 2026

Zapata Quantum is collaborating with NVIDIA to apply agentic AI to automate quantum resource estimation workflows, targeting applications in quantum chemistry, drug discovery, energy and advanced materials development. The initiative aims to address a major bottleneck in quantum algorithm development. The companies are developing an automated system that combines AI orchestration, verified quantum workflows and AI feasibility modelling using NVIDIA Agent Toolkit software. The approach has been tested in homogeneous catalysis, building on Zapata's work from the DARPA Quantum Benchmarking programme. Zapata has filed a provisional patent application related to an "agentic framework for quantum". The company, which trades on OTCQB under ticker ZPTA, holds over 60 granted and pending patents in quantum software and participates across all technical areas of DARPA's Quantum Benchmarking programme.