Graduate of a Federal University with a degree in Physics and Computational Data Analysis.

At Apex AI Automation Solutions, I architect and deploy end-to-end autonomous systems that transform raw data into enriched assets and Read more revenue-scaling workflows. My focus is on eliminating manual operational bottlenecks through advanced multi-platform integration and generative AI Key Achievements: ​System Orchestration: Designed multi-stage n8n workflows managing complex API data flows. ​Intelligence & Assets: Engineered Groq-powered engines for semantic analysis and integrated Stability AI (SD3) for automated, high-fidelity asset generation. ​Advanced Problem Solving: Resolved binary data mapping errors using custom JavaScript and bypassed OAuth 2.0 "redirect_uri_mismatch" hurdles to ensure 24/7 reliability. ​Quality & Impact: Implemented "Human-in-the-Loop" gates, reducing processing time by 95% while maintaining 100% data integrity.

A client wanted a SaaS solution that could manage user subscriptions, secret codes, and cloud-based data storage using Supabase. They were struggling Read more because previous attempts had data syncing issues, secret codes weren’t validating properly, and their app kept breaking when scaling users. The client was frustrated users couldn’t redeem codes, data was inconsistent, and the workflow was unreliable. They needed a solution that could handle growing traffic without constant manual fixes. I approached the problem step by step: Analyzed the workflow: I mapped out how secret codes should be generated, validated, and stored. Configured Supabase Cloud: Set up the database and authentication rules, ensuring secure and scalable storage. Integrated the SaaS logic: Connected Lovable to the cloud database, allowing real-time validation and redemption of secret codes. Tested & debugged: Simulated multiple users, fixed syncing issues, and ensured codes worked under all scenarios. Optimized for scalability: Implemented error handling and efficient queries to handle large user loads without crashing. The result: a fully functional SaaS system where secret codes work seamlessly, data stays consistent, and users experience smooth, reliable operations. SaaS development requires careful integration between cloud databases, app logic, and user workflows. Small misconfigurations can break the user experience, but structured testing and proper cloud setup make the system reliable and scalable.

A client reached out frustrated because their n8n workflow had completely stopped working. They were trying to connect an OpenAI API key to n8n Read more credentials, but one digit was missing and their account didn’t have the required $5 credit. On top of that, another API had been set in the console, but the product wasn’t enabled, causing the workflow to fail entirely. The client was confused, stressed, and worried about losing leads and data. They had tried multiple fixes but nothing worked. I approached the problem step by step: Diagnosed the workflow: I traced the errors in n8n and identified that both API misconfigurations were causing the failures. Fixed the OpenAI API key: Corrected the missing digit and ensured the account had sufficient funds for operations. Configured the console API: Enabled the required product and validated all credentials. Tested the workflow end-to-end: I ran multiple simulations to ensure data was collected, filtered, and routed correctly. Optimized the workflow: Added checks and proper error handling to prevent similar issues in the future. After these steps, the workflow came back alive, running smoothly. Submissions were updating in Google Sheets, messages were being sent correctly, and the client’s automation was fully restored. Lesson Learned: Small mistakes in API setup missing digits, insufficient credit, or disabled products can break entire systems. Careful setup, validation, and testing are critical to reliable automations.