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AI Chatbots
Conversational agents that handle support, sales, and internal workflows around the clock.
We design intelligent AI systems that automate business processes, optimize operations, and transform data into actionable insights.

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Conversational agents that handle support, sales, and internal workflows around the clock.
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Visual inspection, detection, and monitoring systems built for industrial and clinical use.
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Text understanding, extraction, and generation tuned to your domain and language.
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Forecasting models that turn historical data into forward-looking decisions.
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Personalization engines that match products, content, and services to each user.
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End-to-end process automation combining AI with existing enterprise systems.
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Pipelines and dashboards that surface the metrics that matter.
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Strategy and architecture guidance for organizations adopting AI at scale.
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A fast, low-input tool that evaluates natural ventilation strategies in office rooms against airborne transmission risk (R0), CO2 concentration and thermal comfort — the whole year read at once, from a handful of early-design inputs.
Saha Arousha Abidar builds artificial intelligence systems for enterprises, institutions, and government bodies — from prototype to deployed platform.
Volume one of the Advanced Topics in Computer Science series, devoted to load management and resource scheduling in cloud environments. The book moves from the foundations of cloud resource models and workload characterisation to classical scheduling policies, metaheuristic optimisation and learning-based schedulers, closing with applied case studies on energy consumption, cost and service-level guarantees. Intended for graduate students, researchers and engineers working on distributed and cloud systems.
A comprehensive reference for the study of heterogeneous biological networks, covering the algorithms, theory, and applications of link prediction — protein analysis, diseases, biological pathways and processes — treated with modern computational models. Written for researchers, students, and specialists in biotechnology, data science, and computer science.
An end-to-end treatment of quantum computation and the algorithms built on it — from the theoretical foundations of qubits, gates and circuits through to applied quantum algorithms and their use in optimization and machine learning.
A practical guide to deep learning built around the Python ecosystem, taking readers from the underlying mathematical and conceptual foundations through to hands-on implementation of neural network architectures. Covers core building blocks, training and optimization, and applied examples suited to students and practitioners moving from theory to working code.
2025
Journal article · peer reviewed
2024
Conference paper
2024
Journal article · peer reviewed
2023
Technical report

Farzad Majidi is an Artificial Intelligence researcher and Quantum Machine Learning specialist. His research and professional work focus on developing next-generation AI technologies that bridge advanced scientific research with real-world industrial applications.
In addition to leading AI research and industrial projects, he authors technical books, publishes international scientific papers, and advances intelligent technologies across quantum and classical computing.
His vision is to accelerate the adoption of AI and quantum technologies by delivering innovative, scalable, and enterprise-ready solutions.
A compact team of machine learning engineers, data scientists, and software architects delivering AI systems end to end — from data pipelines to deployed production services.
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