AI-based data collection and content processing solution reduces contract costs by 19%

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For a global consumer technology leader

“When dealing with processing data POIs that span million touchpoints, delivering on quality, reliability and scalability has to become a habit – every time”

– A global technology leader seeking unified knowledge access

When a world’s leading consumer technology provider wanted to optimize POI management with data accuracy and correctness at speed and scale, Movate’s AI-powered data processing and content management solution delivered transformational impact:

On SLAs for the last 9 months

Volume handling within 4 weeks of onboarding

Cost reduction

7.2% > 2.8%

Defect rate reduction achieved

Business problem

As digital maps become the backbone of critical services across logistics, mobility, commerce, and smart infrastructure, map data providers are under immense pressure to deliver precise, accurate, and high-density Point of Interest (POI) data in real time. Users today expect seamless experiences that depend on precision and geographic completeness, driving the need for providers to go beyond traditional data collection methods. However, maintaining high standards in POI quality while ensuring speed and scale poses significant technical and operational challenges.

Most providers work with massive POI datasets involving millions of parameters for generation and extraction. The complexity is compounded by the need to automate ingestion pipelines, apply reliable categorization heuristics, and enforce strict annotation rules—all while ensuring these systems can scale without performance degradation. The high velocity of policy and data updates further intensifies the demand for robust quality assurance mechanisms, leaving little room for manual oversight. Unfortunately, many players in the industry are still relying on fragmented systems without centralized platforms or knowledge repositories, leading to inefficiencies, stagnation, and delayed delivery cycles.

To remain competitive and meet ever-evolving client expectations, map data providers must embrace modern technology solutions. This includes investing in AI-driven automation, scalable data optimization engines, and platforms that retain operational knowledge. With growing demands from both B2B and B2C clients for clean, contextual, and validated POI data, the need for intelligent tooling and advanced infrastructure is not optional—it’s table stakes.

Customer challenge

Our client provides map data and POI information to business enterprises.
Map data providers face numerous challenges in delivering high-quality Point of Interest (POI) data, especially as expectations for accuracy, freshness, and geographic coverage grow.

Maintaining data accuracy is a constant struggle due to rapidly changing physical environments, inconsistent source data, and lack of standardized formats. Though the client relies on technology stacks such as GIS systems, ML models, NLP engines, and computer vision for image-based POI extraction, the sheer velocity and demand poses challenges with quality, speed and scale.

Despite these tools, managing structured and unstructured data at scale while ensuring high-frequency updates and geographic completeness remains resource-intensive and error-prone. Additionally, the absence of centralized knowledge repositories or automation frameworks further hinders their ability to scale operations effectively and meet real-time demands.

Movate’s AI solution

To address the increasing complexity and precision demands of POI (Point of Interest) data management, a value-driven and technically robust solution was implemented. This began with strategically reducing contract values by boosting productivity through innovation, thereby delivering long-term business value without compromising on quality. Glide path targets were established based on work nature and employee experience to streamline workflows. A standardized data validation framework was introduced to ensure consistency and accuracy across POI datasets, while the 5-Why Root Cause Analysis methodology, coupled with performance-based incentives, helped resolve systemic issues and drive continuous quality improvement.

To support knowledge continuity and operational efficiency, a centralized knowledge management system was created to capture and scale best practices. Additionally, team structures were optimized, and the EASE (Efficiency, Accountability, Scalability, Execution) operational model was implemented to stabilize delivery processes. This comprehensive solution enabled the provider to meet high client expectations with scalable, reliable, and cost-effective POI data services for mission-critical mapping platforms.

Movate AI differentiator

This automated solution leveraged the Movate AI Framework to improve map data collection, process new and updated policy documents, improve data accuracy and consistency of POI data, and improve validation standards through crowd sourcing.

With deep domain expertise, data acquisition, correlation, management, mapping, reporting, spatial analytics, and enterprise-grade integrations using Azure AI and Cognitive Services, Movate AI empowered this consumer technology leader to transform data and POI management to deliver productivity, quality, and reliability at speed and scale.