From Gut to Graph: Building Netflix’s External Intelligence Engine

Himanshu Singh, an Engineering Manager at Netflix, led the development of a transformative data product that is now foundational to how the company makes multi-billion-dollar content and strategic business decisions.

Before this innovation, many critical decisions at Netflix—such as whether to greenlight a script, license a film, or adjust pricing in global markets—were heavily dependent on human judgment, tribal knowledge, and fragmented data. There was no scalable system for incorporating rich external signals like reviews, ratings, search trends, and public interest into a consistent, trustworthy decision-making framework.

Himanshu envisioned a platform that could bridge creative instinct with structured intelligence. He architected a system that ingests and integrates data from numerous public sources, then transforms it into a structured, queryable format. By connecting entities such as movies, actors, companies, and entertainment themes, the product enables deep, real-time visibility into the entertainment landscape across hundreds of countries and decades of historical context.

Beginning as an individual contributor, Himanshu built the core architectural components, including ingestion pipelines, entity resolution algorithms, and semantic modeling. After transitioning into a leadership role, he scaled the platform significantly—evolving its infrastructure, improving onboarding speed, and enabling wider adoption across the company. He led a high-performing, cross-functional team of engineers, data scientists, and analysts to embed this capability into decision workflows across multiple business units.

Today, the platform supports predictive models and operational tools used in script evaluation, content valuation, market strategy, competition analysis, and personalization. It has dramatically reduced time-to-insight, turning days of fragmented research into instantaneous, explainable outputs.

Himanshu’s achievement lies not only in building a robust technical system, but in translating vision into lasting organizational value. His work demonstrates how thoughtful data architecture and engineering leadership can elevate both creative decision-making and business performance in one of the world’s most dynamic industries.