Shared Memory for AI Tools

Harper’s inclusion highlights a broader shift toward integrated cloud-native platforms that unify data, caching, messaging, and application logic. The article explains how Harper’s distributed runtime and managed infrastructure reduce operational complexity, improve performance, and support modern applications and AI agents that require fast, reliable access to state, events, and tools.

Harper Recognized as an Honorable Mention in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

News

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

Harper 5.2: More Throughput per Node, Fewer Systems Around It

Explore vector index in Harper 5.3’s with benchmarks against pgvector and Harper 5.2, and the open-source Node.js package @harperfast/hnsw.

Harper Cortex provides a shared memory layer for AI tools and agents, unifying context across assistants like Claude, Cursor, and Copilot while storing structured knowledge in a vector index on Harper.

Download

Explore Recent Resources

Comparison

Faster Vector Search in Harper 5.3 with Native HNSW

Comparison

Explore vector index in Harper 5.3’s with benchmarks against pgvector and Harper 5.2, and the open-source Node.js package @harperfast/hnsw.

Kris Zyp

SVP of Engineering

Comparison

Blog

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

Aleks Haugom

Senior Manager of GTM

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

What If Your AI App Didn’t Need All Those Services?

Oct 2026

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

What If Your AI App Didn’t Need All Those Services?

Explore how Harper brings search, embeddings, model access, and controlled AI decisions into one runtime, reducing the services around your AI application.

What If Your AI App Didn’t Need All Those Services?

Build a MOP and change management application on Harper. Connect procedures, search, approvals, and execution without assembling a separate infrastructure stack.

How to Build a MOP and Change Management Application Without Stitching Together a Stack

Blog

Build a MOP and change management application on Harper. Connect procedures, search, approvals, and execution without assembling a separate infrastructure stack.

Aleks Haugom

Senior Manager of GTM

Build a MOP and change management application on Harper. Connect procedures, search, approvals, and execution without assembling a separate infrastructure stack.

How to Build a MOP and Change Management Application Without Stitching Together a Stack

Sep 2026

Build a MOP and change management application on Harper. Connect procedures, search, approvals, and execution without assembling a separate infrastructure stack.

How to Build a MOP and Change Management Application Without Stitching Together a Stack

Build a MOP and change management application on Harper. Connect procedures, search, approvals, and execution without assembling a separate infrastructure stack.

How to Build a MOP and Change Management Application Without Stitching Together a Stack

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Blog

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

Austin Akers

Head of Developer Relations

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

System Design

Blog

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

Austin Akers

Head of Developer Relations

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Harper Argues Against the Multi-System Stack and Releases 5.2

Media Coverage

Renato Losio

InfoQ Staff Editor

Harper Argues Against the Multi-System Stack and Releases 5.2

Renato Losio

Harper Argues Against the Multi-System Stack and Releases 5.2

Renato Losio