AI Agent-Based Data Enrichment for Construction Leads
Case Studies
Challenges & Solutions
Technical Environment
Results
Executive Summary
Client
A Major Modular Workspaces Company
Industry
Manufacturing, Engineering, Transport & Logistics
Business Problem
Third-party construction lead data was incomplete and not immediately actionable. Sales and marketing teams needed faster access to project details for lead qualification and outreach planning.
Outcome
AI-powered agents automated lead enrichment and improved the quality, completeness, and usability of construction project data.
Challenges
- Lead data required additional enrichment.
- Manual research took significant time.
- Key project details were not always available.
- Marketing teams needed faster lead prioritization.
- Sales teams needed more actionable insights.
- Data enrichment had to scale across multiple records.
- Enriched data required structured storage.
- Lead visibility and accuracy needed improvement.
Solutions
- Integrated third-party lead data with AI-powered web search agents.
- Integrated third-party lead data with AI-powered web search agents.
- Captured project value, size, bid dates, status, location, and contact details.
- Stored enriched data in Snowflake.
- Enabled downstream access for sales and marketing teams.
- Improved lead qualification, prioritization, and outreach planning.
- Reduced manual research dependency.
Technical Environment
- AI Agent-based data enrichment solution
- OpenAI Agents SDK with web search tool use
- Third-party Construction project lead data
- Snowflake
- AWS deployment
- Scheduled or manual triggers with failure handling
- Automated run-report delivery through SNS
- Downstream consumption through Snowflake jobs
Results
- Processed 1,500 records per day in under 10 minutes
- Achieved an 82% fill rate for important fields
- Reduced manual lead research effort
- Improved lead data quality
- Enabled faster opportunity identification
- Improved outreach planning and sales readiness