Harper, bringing “next-level web performance to a digital-first world,” is releasing version 4.6 of its composable application platform, featuring several enterprise-grade components, chief among them the addition of vector indexing for the efficient storing and retrieving of high-dimensional vector data. For large digital brands with extensive product catalogues, the introduction to AI-enhanced search helps accelerate the customer’s journey and time-to-purchase.
“There’s no question, AI is transforming the search box into an intent box,” said Stephen Goldberg, CEO and co-founder of Harper. “Enabling semantic cache allows companies to do more than just deliver results—they can respond quickly with the right recommendations, products, and advice to improve customer satisfaction and drive conversion rates. Harper helps accelerate everything in your web experience, from contextual decision-making of AI to the consumer’s purchase journey overall.”
According to the company, Harper’s low-latency architecture and superior performance capabilities are attractive features for large digital brands with high-volume websites.
The composable application platform integrates a high-performance database, application server, caching and messaging functions into a single runtime instance, eliminating the need for separate technologies.
By keeping data at the edge, Harper lets applications avoid the transit time of contacting a centralized database. Layers of resource-consuming logic, serialization, and network processes between each technology in the stack are removed, resulting in extremely low response times that translate into greater customer engagement, user satisfaction, and revenue growth, the company said.
The vector indexing feature found in Harper v. 4.6 powered by the Hierarchical Navigable Small World (HNSW) algorithm, allows for quick and accurate nearest-neighbor search, which is essential in applications such as recommendation systems, personalized content feeds, chatbot retrieval, image recognition, and natural language processing.
The addition of vector indexing to the Harper platform eliminates the need for third-party vector databases as semantic caching can be done natively in Harper, helping bring down the overall costs of running AI models.
Other notable features found in the latest release of the performance platform include:
- New plugins API with support for dynamic loading
- HTTP logging for improved formatting, control and debugging
- New data loader for pre-loading content
- Resource API updates
To learn more about these new features visit the Harper v. 4.6 release notes here.
For more information about this news, visit www.harpersystems.dev.