01. InsureflowAi
[01] PROBLEM STATEMENT
The insurance industry requires "Page-to-Data" extraction with surgical precision from highly heterogeneous PDF documents. Traditional OCR solutions prove incapable of maintaining logical structure across variable layouts (complex tables, nested hierarchies). This technological gap forces time-consuming, costly, and error-prone manual data entry, hindering the automation of critical business processes.
[02] TECHNICAL SOLUTION
Cascading model architecture: documents undergo initial filtering via XGBoost. Structural analysis (Layout Analysis) relies on a fine-tuned TATR model to accurately isolate tables. Hierarchy is reconstructed by a classification model factoring in layout and header semantics. Coverage lines are then normalized via a lightweight language model, specialized in French healthcare terminology. Everything is packaged in a standalone Windows executable: the entire pipeline runs locally on the client machine to ensure total privacy and eliminate cloud infrastructure costs.
[03] OPTIMIZATION / METRICS
The tool integrates a "Human-in-the-loop" mechanism with confidence scoring: each extracted cell is evaluated, and a color code guides the user to data requiring priority verification. Currently developed in Python, the solution is being migrated to a Rust / Tauri architecture. This rewrite aims to minimize the desktop application's memory footprint and ensure ultra-fast local inference performance, aligning with the sector's responsiveness requirements.
02. Layer0
[01] PROBLEM STATEMENT
For a freelancer or small manufacturing workshop, managing a fleet of 3D printers quickly becomes a logistical challenge. True profitability is often blurry: between filament costs, invisible component wear (nozzles, belts), and power consumption, the cost price is frequently underestimated. Without a centralized tool, the craftsman loses precious time on administrative management instead of producing, directly impacting their growth.
[02] TECHNICAL SOLUTION
Containerized Nuxt 3 / Node.js architecture via Docker. The data flow relies on .gcode file ingestion: the user uploads their prepared file, triggering high-performance selective parsing. The algorithm analyzes machine instructions to extract critical metadata (prep time, print time, filament consumption) before injecting them into a PostgreSQL database. This process ensures precise indexing of each print job, transforming a simple manufacturing file into actionable accounting data.
[03] OPTIMIZATION / METRICS
The calculation dynamically integrates the complete economic model: machine depreciation, electricity, mechanical wear, and material cost to provide preventive alerts.
03. Trading SDK & Bridge
[01] PROBLEM STATEMENT
The native MetaTrader 5 API is restricted to the Windows ecosystem, lacks object abstraction, and exhibits chronic instability during prolonged executions. Developing cross-platform trading algorithms (macOS/Linux) requires a wrapper capable of securing data flows and normalizing interactions with the MetaTrader5 terminal.
[02] TECHNICAL SOLUTION
Development of an Algo-Trading SDK designed as a high-performance Wrapper Engine. The solution creates a logical "Bridge" allowing execution of complex strategies via structured Python objects. The architecture supports sending orders and retrieving real-time data while breaking free from OS constraints and the official MetaTrader5 library, transforming a low-level API into a modern and predictable development tool.
[03] OPTIMIZATION / METRICS
Priority was given to Resource Safety and network socket integrity. Implementation of rigorous Design Patterns, utilizing Context Managers (with) and magic methods (__enter__, __exit__) to ensure systematic opening and closing of connections.
This approach prevents any resource leaks or socket blocks, which are critical pain points during high-frequency or long-term trading sessions.
__enter__ / __exit__
04. Equicares
[01] PROBLEM STATEMENT
Democratizing biomechanical analysis for riders via a centralized management platform. The challenge was to transform session photographs into actionable coaching advice, while centrally managing a stable's health, nutritional, and administrative tracking.
[02] TECHNICAL SOLUTION
SaaS platform integrating a hybrid AI stack. Posture analysis relies on YOLO (Pose Estimation) to extract articular Keypoints from imported snapshots. A vector algebra layer calculates the critical angulation θ, whose coordinates feed an LLM via a structured prompt to generate personalized coaching. In parallel, the backend manages nutritional calculation and care planning modules.
[03] OPTIMIZATION / METRICS
The solution validated interoperability between Computer Vision and GenAI on real-world use cases. While static analysis was rolled out, an R&D module on video analysis was conducted to explore dynamic movement before the project's shutdown. This post-mortem highlighted the critical importance of Product-Market Fit when dealing with a highly dense technical solution.
> CAREER_SEQUENCING
> Design of AI architectures specialized in data extraction (InsureTech sector).
> Lead Dev SaaS Equicares && OpenSource Layer0 / MT5 Bridge.
> Micro-services architecture and optimization of user experience (UX/UI) on business ERP.
> Management of asynchronous data flows via RabbitMQ and Redis.
> Stack: Nuxt 3, Ruby on Rails, RabbitMQ and Redis, PostgreSQL, Docker.
> Analysis and resolution of breakdowns on critical embedded systems.
> Multiplex network diagnostics and high-precision mechanical troubleshooting.
> Technical right-hand: supervising adherence to manufacturer standards and recall campaigns.
> Managing complex cases in direct contact with BMW support engineers.
> Methodological rigor applied to high-responsibility environments.
> ACADEMIC_TIMELINE
> Data Specialization: ML model development, Data Visualization, Statistics.
> Mobile and API Development (C#, Flutter, Swift, Python) && Linux Administration.
> Customer needs analysis && Software architecture design.
> Deployment automation and continuous integration (CI/CD).
> Statistical modeling and implementation of Machine Learning algorithms.
> Data cleaning and preprocessing.
> Exploratory data analysis and visualization.
> Valedictorian.
> Complex diagnostics and troubleshooting on critical embedded systems.
> Multiplex network analysis and technical incident management.
> Operational rigor applied to Premium vehicle maintenance.