# AquilaX Joins NVIDIA Inception

<figure><img src="https://53914109-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FjAmSnvnfbHl4EDK56iDo%2Fuploads%2Fgit-blob-c75142a725c41cf4562e833838d46892d8ef5330%2FAquilaX-NVIDIA.png?alt=media" alt=""><figcaption><p>AquilaX joins NVIDIA Inception</p></figcaption></figure>

### AquilaX has joined [NVIDIA Inception](https://nvda.ws/2BvtUc9), to accelerate building Security Models for modern software developing.

Joining NVIDIA Inception will help AquilaX to accelerate by train and serve AI Models with higher context awareness. The program will also offer AquilaX the opportunity to collaborate with industry-leading experts and other AI-driven organizations.\\

With the program, we aim to accelerate training and fine-tuning of Securitron v3, the next-generation AI model powering AquilaX’s vulnerability detection engine. This project will leverage H100 nodes to:

1. Ingest and process an expanded dataset of 500M+ code samples, CVEs, and triaged vulnerabilities.
2. Enhance multi-modal understanding, integrating source code, configuration files, and natural language bug reports.
3. Improve real-time contextual reasoning, enabling near-zero false positives with accurate remediation suggestions.
4. Optimize for inference speed and memory footprint to support CPU-bound enterprise environments.

Our goal is to release a significantly more accurate and efficient AI model within 60 days, integrated into AquilaX’s AppSec platform for immediate customer benefit.

NVIDIA Inception helps startups during critical stages of product development, prototyping and deployment. Every Inception member gets a custom set of ongoing benefits, such as [NVIDIA Deep Learning Institute](https://www.nvidia.com/en-us/deep-learning-ai/education/?ncid=em-ded-n1-96486) credits, preferred pricing on NVIDIA hardware and software, and technological assistance, which provides startups with the fundamental tools to help them grow.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aquilax.ai/blog/announcements/aquilax-joins-nvidia-inception.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
