How Did PlanHub Revolutionize Subcontractor Onboarding Using AI?

We helped PlanHub streamline subcontractor onboarding by implementing an AI-powered solution that transformed unstructured documents into clean, structured data-reducing manual effort, improving accuracy, and accelerating onboarding at scale.

At a glance

Industry
Software/Construction
Location
U.S

Successive Highlight

95%

Improvement in trade mapping precision

60%

Fewer hours spent on subcontractor data cleanup

About Client

PlanHub is a leading U.S. platform helping general contractors, subcontractors, and suppliers connect and collaborate during preconstruction and bidding. While it digitized bid posting, document sharing, and communication, subcontractor onboarding remained manual, inconsistent, and error-prone. This slowed projects and limited trade-level insights. To stay competitive, PlanHub turned to AI-driven automation instead of adding more manpower across its growing network nationwide.

About this project

This project set out to transform how subcontractor data moves through the PlanHub ecosystem. The team aimed to convert unstructured files into clean, reliable intelligence that GCs could use instantly. The solution needed to read Excel and CSV uploads automatically, validate and standardize subcontractor details, map trade descriptions accurately to CSI Division codes, and plug seamlessly into existing onboarding workflows. The outcome would be a smoother, smarter data pipeline, giving every GC consistent, ready-to-use subcontractor information from day one.

Solutions Implemented

The AI solution automated subcontractor data onboarding through smart file parsing, intelligent data cleaning, AI-driven trade classification, and secure system integration. It transformed messy uploads into structured, validated, and analytics-ready records-improving accuracy, governance, and operational efficiency across PlanHub’s platform.

Smart Upload & Parsing:

General Contractors can now upload subcontractor lists in Excel or CSV format. The AI parsing engine detects file structure automatically and extracts essential details such as company name, contact info, trade, and address.

Automated Data Cleaning:

The AI engine processes each record to extract and standardize data, normalizing contact details, validating key fields like company name and trade, and identifying and merging duplicates for clean, reliable subcontractor information.

Intelligent Trade Mapping:

Using Kagen’s GenAI models, the solution intelligently interprets trade descriptions and keywords to accurately assign the correct CSI Division Name and Code, achieving over 95% accuracy and enabling consistent trade classification for analytics and reporting.

Integrated Data Governance:

All processes run through secure APIs integrated with PlanHub’s backend, enabling role-based data access, maintaining complete audit trails for every parsing and mapping action, and ensuring full compliance with internal validation and governance standards.

Providing results that exceeded the client’s expectations

Trade mapping precision improved by 90–95%, significantly enhancing classification accuracy and overall subcontractor data reliability.

Subcontractor profile setup became twice as fast for general contractors, accelerating onboarding and reducing manual processing time.

Mismatched trade and contact records decreased by 70%, improving overall data quality and platform reliability.

Data became fully standardized and analytics-ready, enabling accurate business intelligence, reporting, and more informed decision-making across teams.

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