AI-Enhanced Massive Reporting Ecosystem: Automating Regulatory Compliance at Scale.

Description: We engineered a hybrid automation engine for Chilquinta Energía that generates over 7,000 technical inspection reports annually. By orchestrating Power Automate, GIS, and a custom Python core, we reduced manual workload by 7,000+ hours/year, using AI to draft technical conclusions and integrate field evidence autonomously.

The Challenge Generating thousands of inspection reports annually was a bottleneck. The manual consolidation of field data (PowerApps), photographic evidence (SharePoint), and cartography (GIS) was slow and error-prone, exposing the company to regulatory fines and consuming valuable engineering hours on administrative drafting.

The Solution We deployed a High-Volume Document Generation Ecosystem that operates on two levels: real-time processing and autonomous bulk generation.

Intelligent Orchestration: A sophisticated Power Automate flow captures field data instantly from PowerApps, triggering real-time email notifications and status updates.

Complex Data Fusion: The system automatically fetches and merges unstructured data: high-res photos from SharePoint and technical sketches directly from Gisred (GIS).

Autonomous Python Core: For massive scalability, we built a custom Python application capable of generating thousands of PDF/Word reports autonomously on demand.

AI-Driven Insights: Beyond simple formatting, the system uses AI to analyze data and draft technical conclusions, ensuring consistency and quality across every report.

Tech Stack & Impact

• Core Engine: Python (Bulk Generation) & Power Automate (Orchestration).

• Integrations: SharePoint, Gisred (GIS), PowerApps.

• The ROI:

  • Efficiency: +7,000 man-hours saved per year (equivalent to liberating an entire team of engineers).

  • Compliance: Drastic reduction in errors and delays, mitigating the risk of regulatory fines.

  • Focus: Shifted team focus from "copy-pasting" to strategic grid analysis.