- Hyperlink runs entirely on local hardware, keeping every search private
- The app indexes massive data folders on RTX PCs in minutes
- LLM inference on Hyperlink doubles in speed with Nvidia’s latest optimization
Nexa.ai’s new “Hyperlink” agent introduces an approach to AI search which runs entirely on local hardware.
Designed for Nvidia RTX AI PCs, the app functions as an on-device assistant that turns personal data into structured insight.
Nvidia outlined how instead of sending queries to remote servers, it processes everything locally, offering both speed and privacy.
Private intelligence at local speed
Hyperlink has been benchmarked on an RTX 5090 system, where it reportedly delivers up to 3x faster indexing and 2x the large language model inference speed compared to earlier builds.
These metrics suggest it can scan and organize thousands of files across a computer more efficiently than most existing AI tools.
Hyperlink does not simply match search terms, as it interprets user intent by applying the reasoning capabilities of LLMs to local files, allowing it to locate relevant material even when file names are obscure or unrelated to the actual content.
This shift from static keyword search to contextual comprehension aligns with the growing integration of generative AI into everyday productivity tools.
The system can also connect related ideas from multiple documents, offering structured answers with clear references.
Unlike most cloud-based assistants, Hyperlink keeps all user data on the device, so the files it scans, ranging from PDFs and slides to images, remain private, ensuring that no personal or confidential information leaves the computer.
This model appeals to professionals handling sensitive data who still want the performance advantages of generative AI.
Users gain access to fast contextual responses without the risk of data exposure that accompanies remote storage or processing.
Nvidia’s optimization for RTX hardware extends beyond search performance, as the company claims retrieval-augmented generation (RAG) now indexes dense data folders up to three times faster.
A typical 1GB collection that once took nearly 15 minutes to process can now be indexed in about 5 minutes.
The improvement in inference speed also means responses appear more quickly, making everyday tasks such as meeting preparation, study sessions, or report analysis smoother.
Hyperlink merges convenience with control by combining local reasoning and GPU acceleration, making it a useful AI tool for people who want to keep their data private.
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