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Turn Browsing into Buying with Edge AI

Discover how Harper’s latest features streamline development, boost performance, and simplify integration. This technical showcase breaks down real-world workflows, powerful updates, and practical tips for building faster, smarter applications.
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Turn Browsing into Buying with Edge AI

Austin Akers
Head of Developer Relations
at Harper
December 16, 2025
Austin Akers
Head of Developer Relations
at Harper
December 16, 2025
Austin Akers
Head of Developer Relations
at Harper
December 16, 2025
December 16, 2025
Discover how Harper’s latest features streamline development, boost performance, and simplify integration. This technical showcase breaks down real-world workflows, powerful updates, and practical tips for building faster, smarter applications.
Austin Akers
Head of Developer Relations

In this conversation, Austin and Ivan discuss the implementation of Edge AI within the Harper platform, focusing on real-time inferencing capabilities, performance metrics, data privacy, and various applications beyond e-commerce. Ivan explains how deploying AI models at the edge can significantly enhance customer experiences by providing faster and more relevant recommendations. They also touch on the importance of community engagement in developing AI solutions and the ethical considerations surrounding data privacy.

In this conversation, Austin and Ivan discuss the implementation of Edge AI within the Harper platform, focusing on real-time inferencing capabilities, performance metrics, data privacy, and various applications beyond e-commerce. Ivan explains how deploying AI models at the edge can significantly enhance customer experiences by providing faster and more relevant recommendations. They also touch on the importance of community engagement in developing AI solutions and the ethical considerations surrounding data privacy.

Discover how Harper’s latest features streamline development, boost performance, and simplify integration. This technical showcase breaks down real-world workflows, powerful updates, and practical tips for building faster, smarter applications.

Download

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Discover how Harper’s latest features streamline development, boost performance, and simplify integration. This technical showcase breaks down real-world workflows, powerful updates, and practical tips for building faster, smarter applications.

Download

White arrow pointing right
Discover how Harper’s latest features streamline development, boost performance, and simplify integration. This technical showcase breaks down real-world workflows, powerful updates, and practical tips for building faster, smarter applications.

Download

White arrow pointing right

Explore Recent Resources

Comparison
GitHub Logo

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.
Cache
Comparison
End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.
Person with short dark hair and moustache, wearing a colorful plaid shirt, smiling outdoors in a forested mountain landscape.
Aleks Haugom
Senior Manager of GTM
Comparison

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.
Aleks Haugom
Jun 2026
Comparison

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.
Aleks Haugom
Comparison

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.
Aleks Haugom
Tutorial
GitHub Logo

Your API cache is secretly a database

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.
Cache
Tutorial
Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.
Person with very short blonde hair wearing a light gray button‑up shirt, standing with arms crossed and smiling outdoors with foliage behind.
Kris Zyp
SVP of Engineering
Tutorial

Your API cache is secretly a database

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.
Kris Zyp
Jun 2026
Tutorial

Your API cache is secretly a database

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.
Kris Zyp
Tutorial

Your API cache is secretly a database

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.
Kris Zyp