About us
AI runs where your business runs – in Java.
Deep Netts is a next-generation AI platform built entirely in Java, designed to bring advanced deep learning directly into the JVM – where most enterprise systems already run.
- 2022
- Founded · grown out of Neuroph
- JSR 381
- Java standard · reference implementation
- 2×
- Java Champions · on the leadership team
- 1000×
- Faster analysis · U.S. DoE Jefferson Lab
Who we are
AI that fits the enterprise.
We help organizations train, optimize, and deploy AI models without the complexity of bridging to Python or other ecosystems. With GPU acceleration, Vector API integration, and enterprise-grade observability, Deep Netts delivers the performance, scalability, and control that modern businesses demand.
By combining years of research and engineering expertise, Deep Netts enables companies to unlock the full potential of AI with faster training, lower cloud costs, and improved energy efficiency. From scientific research and manufacturing to retail and finance, enterprises use Deep Netts to power intelligent systems that are efficient, secure, and production-ready.
We are proud to collaborate with leading organizations including the U.S. Department of Energy's Jefferson Lab, University of Minnesota, and the Java Community Process, helping advance the next era of Java-native AI.
At Deep Netts, we believe that AI should fit the enterprise – not the other way around.
Our story
From a university lab to the Java standard for AI.
- 2004
Doctoral research on a Java neural network framework – the seed of Neuroph.
- 2013
Neuroph wins the Duke's Choice Award at JavaOne; Zoran Ševarac named Java Champion.
- 2017
JSR 381 Visual Recognition API launched at the JCP, co-led with Frank Greco.
- 2022
Deep Netts Inc founded. JSR 381 final release, with Deep Netts as reference implementation.
- 2023
JCP Member of the Year award for the work on Java and machine learning standards.
- 2025
JavaOne San Francisco: 5000× faster scientific data analysis at Jefferson Lab.
- 2026
Featured in the JavaOne keynote. Deep Netts 4.0 brings FFM and Vector API acceleration.
The idea for Deep Netts was born in 2022, while working on Neuroph, an education software for neural networks. After achieving strong results on this project with his university team, Deep Netts' co-founder Zoran Ševarac was inspired to seek a similar solution for the enterprise environment.
Recognizing the challenges enterprises face in integrating AI into their Java systems, Zoran envisioned a platform that facilitates seamless AI integration, transforming high-fixed-cost solutions into scalable operational expenses.
Zoran Ševarac, a Java Champion, esteemed professor at the University of Belgrade, and AI researcher, is a Duke's Choice Award winner with over 20 years of experience in AI and software development, and co-author and expert group co-lead of the Visual Recognition API (JSR381) standard for machine learning-based image recognition that determines how Java applications talk to AI.
With his passion and deep understanding of neural networks, deep learning, and software engineering, combined with his extensive experience leading teams of experts, Zoran has managed to bridge the gap between AI complexities and the needs of Java developers across various sectors, including business, academia, and government. As presented at the JavaOne 2025 Conference in San Francisco, Deep Netts has brought a breath of fresh air to the Java community, empowering modern Java for the AI revolution.
But Deep Netts isn't just about technology; it's a purpose-driven company committed to accelerate implementation of AI in the world by empowering major industries and sectors in the AI race, while advancing democratization and positive societal impact of AI.
Leadership
The people behind Deep Netts.

Zoran Ševarac, PhD
Co-founder & CEO
Java Champion · JCP Executive Committee
AI researcher, Java Champion and Full Professor at the University of Belgrade – creator of Neuroph and co-spec lead of the JSR 381 Java standard.

Jelena Ševarac
Co-founder & COO
Business Strategy · Product Strategy
Business strategist who leads business and product strategy at Deep Netts, turning Java-native AI into measurable enterprise value.

Nikola Tomašević
Co-founder & Partner
Enterprise Partnerships · Licensing
Lawyer and entrepreneur with 20+ years across legal practice, finance and cross-border business – leads enterprise adoption, partnerships and licensing at Deep Netts.

Frank Greco
Strategy Advisor
Java Champion since 2000 · NYJavaSIG Founder & Chairman
Senior AI/ML strategist and Java Champion – founder of the world's first Java User Group and co-spec lead of JSR 381 – with a career spanning Google, Bell Labs, NYSE and Sun.
“Deep Netts is definitely the best starting place for someone trying to implement platform-independent neural networks.”
- 1000×
- Faster processing
- +12–15%
- Track reconstruction efficiency
- +15–35%
- More physics statistics
Recognition
Recognised by the Java community.
- 2013OracleDuke's Choice Award
Oracle's award for the most innovative software on the Java platform, for Neuroph.
- 2018Java Community ProcessJSR 381 – Most Significant JSR
JCP recognition for bringing a standard machine learning API to Java.
- 2023Java Community ProcessJCP Member of the Year
Awarded to Zoran Ševarac and Frank Greco for JSR 381.