Business Need

Businesses in Nigeria and Saudi Arabia faced significant challenges accessing accurate, structured, and up-to-date company data from public and online sources. Manual data collection methods were time-consuming, inconsistent, and unscalable. This resulted in incomplete datasets that hindered decision-making, compliance, and customer engagement.

Challenges

Data Availability
Company details such as contact information, year founded, and employee count were scattered or unavailable, especially for small and mid-sized businesses.

Accuracy Requirements
Delivering enriched company profiles with a minimum accuracy threshold of ≥90% to meet Service Level Agreements (SLAs).

Source Variability
Data originated from heterogeneous sources like Google Knowledge Panels and official websites, each with unique structures and inconsistent formats.

High-Volume Processing
Processing and enriching 60,000 company records within tight deadlines while maintaining consistency and reliability posed a major operational challenge.

XDAS Approach

Automated Data Extraction: Set up workflows to crawl and extract data from official websites and Google Knowledge Panels.

API Integration: Integrated with third-party APIs and databases to fill in key fields like financials, social links, and employee count.

ML-Based Enrichment: Employed machine learning models to cross-reference and validate company attributes.

Data Standardization & Cleansing: Normalized and transformed incoming data into a unified format for easier analysis and integration.

Manual Gap Filling: Human experts stepped in to complete missing data where automation fell short, ensuring accuracy thresholds were consistently met.

Quality Assurance: Process Excellence Group conducted multi-layered QA and validation checks to ensure data accuracy and consistency..

Secure Delivery: Final data was delivered in structured formats via secure FTP or email.

Results

With XDAS, automated data enrichment was carried out for 60,000 companies across Nigeria and Saudi Arabia using AI and automation with a Human-in-the-Loop approach. The solution delivered accurate, actionable company profiles and now serves as a scalable model for global data enrichment initiatives.

• ≥90% Data Accuracy Achieved
  The project consistently met its data accuracy SLA through automation, AI, and human verification.
  
• Comprehensive Data Coverage
  Delivered detailed profiles with fields like company size, line of business, contact info, social presence, and leadership.
• Automation Saved Time & Cost
  Automated enrichment and data pipelines dramatically reduced manual workload and operational costs.
• Scalable Infrastructure
  Cloud-based, distributed processing enabled parallel handling of 60,000+ records with minimal latency.