How Srikanth Jonnakuti is Architecting the Future of Digital Real Estate and Financial Equity

In an era where digital transformation often prioritizes operational efficiency over consumer empowerment, Srikanth Jonnakuti stands out as an architect of systems that deliver both enterprise resilience and consumer equity. As a Staff Software Engineer and Cloud Architect at Move, Inc., the operator of Realtor.com, Jonnakuti has engineered some of the most consequential platforms in the digital real estate sector.

Move, Inc. is a key subsidiary of News Corp (Nasdaq: NWS, NWSA), a global media and information services powerhouse that includes iconic brands such as Dow Jones (publisher of The Wall Street Journal), HarperCollins Publishers, News UK, and REA Group. Operating within this Fortune 500 ecosystem, Jonnakuti’s work does not just serve home buyers; it acts as a technological blueprint for one of the world's most influential media conglomerates.

Democratizing Financial Equity at Scale: The Tax Protesting Resource

At the forefront of Jonnakuti’s recent achievements is his role as Lead Architect for the Tax Protesting Resource, launched in April 2025. This strategic national platform addresses a critical but often overlooked issue: property tax overassessments. By engineering a microservices-based ingestion pipeline capable of processing hundreds of millions of county tax records annually, Jonnakuti created a system that democratizes access to financial data.

The platform utilizes proprietary algorithms to identify discrepancies between effective tax rates and local market values. The economic implications are massive: the system has identified an aggregate potential saving of over $43 billion in disposable income for U.S. homeowners. In high-cost markets like California, the platform creates pathways for nearly half of all property owners to potentially save a median of $1,875 annually. By transforming complex, disparate government data into actionable financial leverage for the average citizen, Jonnakuti has demonstrated how enterprise-grade data engineering can directly benefit the public good.

A Blueprint for the News Corp Ecosystem

Jonnakuti’s impact extends far beyond Realtor.com. His architectural innovations have served as reference implementations for the broader News Corp network, which seeks to unify technology across its diverse global portfolio.

Cloud Efficiency (CloudOpt): Facing the industry-wide challenge of spiraling infrastructure costs, Jonnakuti architected CloudOpt, an intelligent orchestration engine that uses advanced bin-packing algorithms to "right-size" compute resources. This system slashed Realtor.com’s annual cloud spend by over $5 million and reduced infrastructure costs by 35 percent. This FinOps methodology offers a strategic template for data-heavy subsidiaries like HarperCollins and Dow Jones, where digitizing vast archives requires massive, cost-efficient compute power. By automating resource allocation, Jonnakuti has freed up capital for reinvestment into content creation and journalism.

Data Sovereignty (SecureGraph): With News Corp operating under strict global privacy laws (GDPR in the UK/Australia, CCPA in the US), data governance is paramount. Jonnakuti’s SecureGraph, a Zero-Trust identity system utilizing Graph Neural Networks, automated complex privacy workflows to mitigate an estimated $5 million in regulatory risk. This architecture provides a scalable model for managing reader privacy across The Times (News UK) and The Australian without hindering the user experience, ensuring compliance does not come at the cost of reader engagement.

Real-Time Agility: His Salesforce Event-Driven Architecture replaced brittle polling with real-time data streaming. In the fast-moving world of financial news, exemplified by MarketWatch and Barron’s, data latency is unacceptable. Jonnakuti’s architecture establishes a standard for high-velocity data ingestion, ensuring subscriber data is synced instantly across digital properties.

Pioneering Research in AI and Data Architectures

Jonnakuti distinguishes himself from typical engineers through his prolific contributions to technical research. His 2022 paper, "Graph Neural Networks for Entity Resolution in Cloud-Native Data Platforms," addressed one of the digital economy's most persistent challenges: resolving fragmented customer identities across distributed, siloed systems.

Unlike traditional attribute-matching methods that often fail in complex data environments, Jonnakuti’s approach leverages the multi-hop reasoning capabilities of Graph Neural Networks (GNNs). By embedding relationships directly into the learning process, his methodology allows systems to detect non-obvious connections between disparate records, such as linking a user's behavior across different devices and IP addresses to a single identity, without exposing raw Personally Identifiable Information (PII).

The impact of this research has been profound and widely adopted:

Reduced Data Redundancy: By utilizing learned embeddings to calculate similarity scores between entity nodes, this architecture has been credited with reducing duplicate customer records by 40 percent in high-volume transactional systems.

Real-Time Scalability: Jonnakuti optimized the GNN inference pipeline to run on Kubernetes-based microservices, enabling real-time entity resolution. This capability was crucial for SecureGraph, where it facilitated accurate "Right to Know" and "Right to Delete" requests across 50+ services, directly translating theoretical innovation into regulatory compliance.

Commercial Growth: Internally, he translated this theory into practice, driving a 10 percent increase in referral revenue (valued at roughly $4 million) by improving lead accuracy and reducing identity fragmentation. This demonstrated that rigorous privacy standards, when architected correctly, can coexist with and even drive commercial growth.

AI-Driven Revenue Intelligence

His influence extends to revenue optimization through LeadIQ, an intelligent lead scoring system built on his proprietary AutoMLInsight framework. By replacing static logic with real-time machine learning, the system achieved sub-100 ms scoring latency and a 1 percent conversion uplift, yielding over $6 million in incremental annual revenue. This system exemplifies Jonnakuti's philosophy of "Invisible AI", sophisticated machine learning that operates seamlessly in the background to enhance business outcomes without introducing latency or complexity for the end user.

A Recognized Global Authority

Jonnakuti’s technical leadership has earned him recognition well beyond his immediate organization. In 2025, he was elected a Fellow of the Soft Computing Research Society (SCRS) and a Full Member of Sigma Xi, The Scientific Research Honor Society. He was also elevated to the grade of IEEE Senior Member, a distinction reserved for the top tier of engineering professionals globally.

His expertise is frequently sought to evaluate the industry's best; he currently serves as an expert judge for the 2025 Globee® Awards for Technology, reviewing breakthrough innovations from startups to global corporations. Furthermore, his published research on scaling Generative AI in regulated industries has influenced engineering teams at major tech firms, including Alphabet Inc., where his microservice blueprints helped reduce inference latency overhead to single-digit milliseconds.

Conclusion

From unlocking billions in value for homeowners to defining cloud standards for a global media empire, Srikanth Jonnakuti is defining the next generation of intelligent software architecture. His work demonstrates that the most powerful technologies are those that solve dual challenges: making businesses more efficient while making the economy more equitable. As enterprises continue to navigate the complexities of AI and cloud scale, leaders like Jonnakuti remain essential to ensuring that digital transformation delivers measurable, lasting value.