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Abstract The primary goal of this invention is to revolutionize production engineering by addressing the challenges of integrating unstructured intervention reports with structured production data. Existing systems are unable to provide a seamless integration that enables comprehensive analysis and decision-making. This solution leverages Generative AI and an end-to-end automated pipeline to transform data handling, optimize intervention planning, and provide real-time insights, ultimately enhancing the efficiency and intelligence of production engineers. The invention employs several interconnected modules. First, the **Data Ingestion Module** collects unstructured intervention reports and structured production data from various sources, including databases and cloud platforms. The **Unstructured Data Handling Module** uses domain-driven Generative AI to extract key performance indicators (KPIs) from intervention reports, converting them into structured data formats. Next, the **Integration Module** unifies structured and unstructured data, synchronizing it in real-time. The **Knowledge Enrichment Module** creates a high dimensional knowledge base using Retrieval Augmented Generation (RAG), allowing for interaction with thousands of reports. The **Visualization Module** provides interactive dashboards for users to explore results, while the **Intelligent Assistant Module** enables engineers to query data in real-time, enhancing decision-making capabilities. The integration of structured and unstructured data allows production engineers to assess intervention impacts comprehensively. By automating the extraction of insights from reports and merging them with production time-series data, the solution provides a holistic view of interventions. The ability to interact with large datasets in real-time through an intelligent assistant enables faster and more informed decisions. Case studies have demonstrated that this approach can identify trends in intervention outcomes, optimize future interventions, and reduce missed opportunities due to incomplete analysis. In one instance, it prevented premature shut-off of oil-bearing zones by analyzing water shut-off (WSO) interventions and recommending an alternative, more effective intervention. This work has been implemented on 1000-page scanned documents combined with daily production rate for more than 20 wells for a field. This solution represents a significant leap in production engineering data. analysis by combining the power of Generative AI with real-time data integration. Its ability to seamlessly process both unstructured and structured data is unmatched in the industry. Unlike existing solutions that rely on separate analysis or manual data handling, this system automates the entire process. The use of Retrieval-Augmented Generation (RAG) technology for enriched knowledge interaction and a real-time visualization platform provides a deeper and more scalable understanding of intervention impacts, offering engineers a powerful tool for optimizing production performance.