Vergo's clients in the construction industry were struggling with fragmented financial data from diverse ERP systems, making accurate revenue forecasting and real-time decision-making nearly impossible. They needed a way to unify this data into a single, intelligent platform.

The objective of our collaboration with Vergo was to build a robust financial management and revenue forecasting platform tailored specifically to the construction industry. Vergo required a solution capable of integrating data from diverse ERP systems, providing a unified and customizable interface for real-time analysis, forecasting, and goal tracking.

Unified Architecture and Data Warehousing: Designed a modular Domain-Driven Design (DDD) architecture hosted on GCP, integrating data from multiple ERP systems. Built an ETL pipeline using Airbyte and dbt to enable seamless data consolidation and transformation, creating a real-time financial data warehouse for Vergo's clients.

Enabled Proactive Financial Planning with AI-Powered Forecasting: Developed a regression-based ML model to predict monthly revenue accurately. Integrated into Retool for easy access, it adapts to changes in project costs and contract sizes—empowering proactive financial planning for construction companies.

Reduced Manual Workload with Intelligent Automation: Developed and deployed intelligent AI agents using n8n and custom Python code. These agents automated critical business workflows, including complex data validations and proactive system alerts, reducing manual overhead and ensuring data integrity across the platform.

Work-In-Progress (WIP) Process and Data Management: Implemented a BigQuery data pipeline with partitioned tables to manage historical and current project data efficiently. Enabled low-cost, on-demand access to WIP metrics for better project tracking.

Projections with Percentage-of-Completion Accounting: Built a projection module to support percentage-of-completion accounting with month-by-month earned revenue calculations. Enabled job-specific adjustments—like contract size edits, end date changes, or exclusions—directly in Retool.

Goals Tracking: Designed a goal-setting system with proration logic, letting users define specific financial targets while the system auto-fills the rest. Simplified forecasting by reducing manual input and improving clarity around goal progress.

Through a unified, data-driven approach that integrates machine learning, ETL, and a DDD-based architecture on GCP, we delivered a scalable forecasting platform tailored for the construction industry. By combining data warehousing (Airbyte and dbt), regression-based revenue forecasting, n8n based AI agents, and a Retool-powered interface, we enabled Vergo’s clients to make informed, real-time financial decisions.

The platform’s adaptability and customizability have established Vergo as a key innovator in financial management for construction, providing unmatched forecasting and goal-setting flexibility.

"I had the privilege of working with Abdul and his team developing our product. From the beginning, they demonstrated exceptional skills not only as developers but also as true product thinkers. They took the time to deeply understand our business goals and user needs, translating them into solutions that exceeded our expectations. Their ability to execute with speed and precision while maintaining the highest quality of code was remarkable. Whether it was tackling complex challenges, integrating user feedback, or delivering under tight deadlines, Abdul and his team consistently went above and beyond. Their collaborative approach and attention to detail made the entire process seamless and enjoyable. I highly recommend Abdul and his team!" – Rich, CEO of Vergo