Saad Lachhab

AI-Powered Financial Auditing Platform. . Developed critical ai-powered backend features for automated financial audit workflows. . Led zero-downtime migration from Azure to OVH. . Implemented comprehensive CI/CD pipeline.

ERP LMS/Digital Adoption Platform (DAP) serving over 1,000+ enterprise users and 10,000+ B2C users. . Architected and deployed scalable ERP-focused LMS and DAP. . Reduced infrastructure costs by 35% while improving system performance by 60%. . Deployed LLM-powered intelligent agents that personalized ERP adoption pathways. . Built CI/CD infrastructure on Azure.

Bootstrapped by implementing growth hacking strategies that led to: . 📈 Scaling the client base from 0 to 70 enterprise accounts, in 7 months. . 🤖 building and deploying 4 innovative, AI-native products, from scratch (legal search engine, legal assistant, contract life cycle management (CLM), regulatory watch).

Achieved rapid traction: scaled to 35,000+ active users and 6,000+ listed products within three months of launch, establishing Placari as a Moroccan digital marketplace for second-hand fashion. . Orchestrated the full company build-up — from ideation, market research, and business planning to the development and launch of a scalable mobile platform tailored to local consumer behaviors. . Led the end-to-end product development lifecycle, leveraging Agile and Lean Startup methodologies to drive fast iterations, user-centric design, and continuous deployment while upholding high standards of stability and user experience. . Architected the mobile platform’s technical stack (React Native, Node.js, Python, Google Cloud), implementing recommendation systems, anomaly detection models, and pricing evaluation algorithms to boost engagement and transaction security. . Designed and executed monetization strategies adapted to the Moroccan market, including commissions, premium listings, and brand partnerships, ensuring sustainable revenue generation from day one. . Established a data-driven culture, continuously analyzing user behavior, funnel metrics, and retention patterns to refine both the product offering and business model, driving market leadership in Morocco’s evolving digital commerce space.

. Developed an AI-powered M&A Co-pilot platform transforming due diligence, risk assessment, and deal sourcing for financial institutions and investment firms. . Engineered advanced AI pipelines leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Knowledge Graphs to automate analysis of financial documents, surface hidden risks, and uncover strategic opportunities. . Integrated semantic search and reasoning agents, enabling stakeholders to query complex financial datasets with natural language while ensuring accuracy, speed, and compliance. . Applied rigorous prompt engineering and fine-tuning of LLMs to adapt models to the financial domain, improving precision in contract parsing, anomaly detection, and regulatory context interpretation. . Collaborated with stakeholders, demonstrating the platform’s potential to accelerate deal cycles and enhance decision-making in high-stakes M&A transactions.

. Led innovation and product design for a SaaS platform and mobile app optimizing supply chain decision-making for retailers and distributors. . Developed advanced AI algorithms for multi-source data extraction, aggregation, and fusion, enabling real-time visibility across fragmented supply chain datasets. . Applied mathematical modeling and constraint optimization techniques to solve complex logistics challenges, providing clients with cost-efficient and sustainable supply chain alternatives. . Directed company operations at the executive level, overseeing finance, strategy, partnerships, and investor relations. . Secured €525K in funding (LOI) from Ventures By Delaware, BPI, and other institutional investors, demonstrating strong business viability and investor confidence. . Established an Agile and data-driven culture, ensuring continuous product improvement, high customer satisfaction, and scalable growth.

. Designed and executed in-flight acoustic measurement campaigns across commercial and private aircraft fleets (A350, A330, A320, etc.), deploying and calibrating over 300 high-precision sensors to capture multi-source acoustic data with maximum fidelity. . Defined measurement architectures, installed and validated advanced instrumentation systems on aircraft, and ensured full compliance with aerospace testing protocols. . Monitored and validated real-time data acquisition during flight tests, ensuring robustness, reliability, and accuracy of measurements under extreme operational conditions. . Led the post-processing and analysis of large-scale acoustic datasets, applying advanced methods in signal processing, anomaly detection, and sound event classification. . Pioneered digital transformation initiatives within the acoustics department by introducing data engineering pipelines, machine learning models, and big data visualization tools, drastically improving analysis speed and predictive accuracy. . Authored comprehensive technical reports synthesizing test results, validation procedures, and recommendations for engineering teams, directly supporting strategic decision-making on noise reduction and aircraft certification.

Bing Bin is a start-up project dedicated to waste management and prevention, especially sorting and recycling. We use artificial intelligence to help you sort better and live better. Incubated at the Innovation Center of the University of Technology of Compiegne. Full sponsorship to attend the European Innovation Academy.

. Developed an advanced acoustic modal analysis software for jet engine noise characterization during test-bench trials, delivering higher precision and efficiency in aeroacoustic measurements. . Engineered the software end-to-end: requirements definition, algorithm design, coding (Python), validation, and integration into existing test environments. . Translated state-of-the-art research into practice, implementing the latest academic methodologies for modal decomposition to ensure cutting-edge accuracy and reliability. . Pioneered a novel approach to analyze fan/OGV (Outlet Guide Vanes) noise interactions, enabling a deeper understanding of complex aeroacoustic phenomena. . Conducted parameter sensitivity studies on real-world test signals, improving robustness of models and enhancing predictive validity. . Optimized microphone array design and placement under strict physical and operational constraints, maximizing data quality while ensuring compliance with aerospace testing standards.

Noise reduction of an exhausting duct in Saint-Gobain Glass factory. Design of a muffler with porous lining: • Characterization of the noise generated by the exhaust duct. • Noise impact on the neighborhood. • Analysis of the existing solutions on the market. • Design of an optimal muffler. Job in partnership with USEC (Université Services Etudes & Conseils), the junior enterprise of the University of Technologie of Compiegne.