A Property Listing Software Solution
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The client operated a real estate platform facing significant operational friction due to the fragmented nature of Multiple Listing Service data. They needed to automate the ingestion of property listings from diverse third-party sources while ensuring strict regulatory compliance. The primary goal was to eliminate manual data processing, enabling the business to scale its regional coverage without increasing administrative overhead or technical debt.
WebMob delivered a robust, automated property listing management engine designed to unify disparate data streams into a single, cohesive ecosystem. By integrating advanced machine learning for schema normalization and a scalable infrastructure for high-volume data ingestion, we enabled the client to process listings from multiple MLS providers seamlessly. This solution replaced manual intervention with an automated pipeline, allowing the client to maintain compliance, optimize image delivery, and scale their operations efficiently.
The client struggled to maintain a unified property database due to the incompatible data structures and restrictive access protocols enforced by various regional MLS providers.
Inconsistent Data Schema Management
Each MLS provider utilized unique field structures, forcing the client to perform extensive manual data normalization to maintain a consistent database for their platform.
We engineered a global field structure and integrated a machine learning-powered schema mapping tool that automatically aligns incoming data, removing the need for manual intervention.
Fragmented Third-Party Integration
The client faced significant technical hurdles when attempting to pull property data from multiple sources, each requiring different exchange protocols and image processing methods.
We implemented a centralized ingestion pipeline that supports standard protocols like RETS and RESO, standardizing data exchange and image processing across all third-party providers.
Regulatory Compliance Complexity
Strict and varying regional regulations regarding property display, address disclosure, and office disclaimers created a high risk of non-compliance for the client's business.
We built a compliance-aware management layer that automatically enforces display rules and disclaimers, ensuring every property listing meets legal requirements before appearing publicly.
WebMob engineered a streamlined onboarding interface for new MLS connections. This allows the client to verify credentials and monitor connection status in real-time, simplifying the expansion of their regional footprint.
We developed a flexible mapping interface that aligns external data fields with the internal schema. This enables the client to resolve mapping discrepancies quickly, ensuring data integrity across the platform.
WebMob implemented an automated background scheduling system that fetches property updates every fifteen to thirty minutes. This ensures the client's platform maintains accurate, up-to-date information without manual oversight.
We built a comprehensive dashboard providing visibility into worker metrics and queue status. This enables the client to monitor system performance and manage horizontal auto-scaling based on real-time workload demands.
The MLS Management platform is built on a cloud-native AWS infrastructure with PHP (Laravel) backend, multiple database systems, and serverless computing for scalable property data processing.
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jQueryThe implementation of an automated, ML-driven architecture allowed the client to transition from manual data management to a fully scalable, compliant, and high-performance property ecosystem.
| Capabilities | Before | After |
|---|---|---|
| Data Normalization | Manual mapping of disparate field structures for every new MLS provider. | Automated schema normalization using machine learning for instant integration. |
| System Scalability | Limited by static infrastructure and frequent rate-limiting bottlenecks. | Horizontal auto-scaling architecture that dynamically adjusts to workload spikes. |
| Compliance Management | High risk of manual errors in displaying required legal disclaimers. | Automated enforcement of display rules and disclaimers for every listing. |
Understood the business goals, user needs, existing workflows, and technical requirements.
Defined the system architecture, technology stack, integrations, and data flow required for the solution.
Built the core platform in agile sprints, integrating APIs, backend services, frontend experiences.
Launched the solution, monitored performance, resolved initial issues, and ensured a smooth transition to production.
Validated functionality, performance, security, and usability before preparing the solution for production.
This solution provided the client with a scalable, automated foundation that significantly reduced operational costs and accelerated their time-to-market for new regions.
Automated data ingestion and schema mapping eliminated the need for manual property record updates.
Simplified onboarding of new MLS providers allows the client to enter new regions in days rather than weeks.
Automated compliance checks ensure all property displays adhere to strict legal and industry standards.
Horizontal auto-scaling ensures the platform remains stable and responsive regardless of data volume.
The MLS Management platform successfully streamlined property data exchange across multiple listing services for the US real estate market. By integrating ML-powered schema mapping, automated cron scheduling, and a scalable AWS infrastructure, the solution enables real-time property synchronization while managing compliance requirements across different MLS providers.
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We utilize a centralized ingestion pipeline that supports standard protocols like RETS and RESO, combined with a custom schema mapping tool to normalize data into a unified format.
Yes, we implement complex scheduling with exponential back-off strategies and private NAT gateways to maintain consistent data flow while respecting provider-specific access limits.
We build compliance-aware logic directly into the data pipeline, ensuring that mandatory disclaimers and display rules are automatically applied to every property listing.
We employ a horizontal auto-scaling policy based on real-time metrics, allowing the system to dynamically increase worker capacity to handle any workload while maintaining state.
The system is designed for rapid onboarding; once credentials are verified through the admin dashboard, the automated schema mapping tool significantly reduces the time required for integration.
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D-U-N-S Number: 860386955
CIN: U74999GJ2016PTC092785
