Users expect products that adapt to them in the moment—interfaces that respond to in-session behavior, recommendations that anticipate needs and preferences, and journeys that feel tailor-made. The payoff is proven:

• Netflix saves $1B+ annually from real-time recommendations
• Spotify doubles app engagement from personalized content recommendations

But product and engineering teams can spend up to 24 months just building infrastructure that requires stitching together Kafka streams to feature stores, maintaining complex stream-processing pipelines, and managing low-latency APIs before they start seeing results.

Download the guide to learn how product teams are shipping real-time, AI-powered experiences in weeks, not years.

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What You’ll Learn

• The hidden costs of DIY personalization beyond engineering time
• How real-time context drives north star metrics for higher engagement, retention, LTV
• The new infrastructure approach that eliminates build-vs-buy tradeoffs and integrates with your existing ML stack
• Proven real-time, hyper-personalization patterns from media streaming, gaming apps, fitness apps, and more