Unlock AI's Full Potential

Join Our 4-Month Incubation Program for Maximum ROI!

San Francisco + Online
Start: December 1, 2023
AI Incubator Topics
Run by experts from

What people say

LinkedIn comment LinkedIn comment LinkedIn comment LinkedIn comment LinkedIn comment LinkedIn comment LinkedIn comment

The AI Incubator is currently accepting applications from established companies eager to leverage AI’s potential in addressing concrete business challenges

We welcome fortune 1000, innovative mid-size companies and b-series startups with industrial challenges and companies who have already started building AI-based systems but face difficulties in delivering value in various industries.


AI Incubator Manufacturing
AI Incubator Machinery


AI Incubator Retail


AI Incubator Telco


AI Incubator Logistics


AI Incubator Energy


AI Incubator Agritech


robotics hand illustration


A brief look at the examples of case studies to apply with...

Online Retailer, Handling Diverse Product Range

Company A grappled with the complex puzzle of warehouse storage optimization. It faced inefficiencies as goods with low turnover rates consumed precious space, and box allocation proved suboptimal, which inflated operational expenses and slowed down order fulfillment.
Leveraging NVIDIA software, including Omniverse for synthetic dataset generation and TensorRT for AI inference, along with hardware such as Siemens IPC 520A based on the NVIDIA Jetson Xavier NX GPU, the team deployed AI models for real-time goods analysis and storage optimization.
Project Highlights
In just three months, our MVP project engineered a system able to recognise incoming goods and ensure optimal storage strategies. The implementation leads to reduction in operational costs, and increase in order fulfillment speed.
Siemens IPC 520A TensorBox
Siemens IPC 520A TensorBox
NVIDIA Jetson Xavier NX GPU
NVIDIA Jetson Xavier NX GPU

Online Retailer, Managing a Vast Array of Products

Company B confronted a persistent challenge involving inaccuracies in order fulfillment. Human errors or incorrect barcode assignments often led to the shipment of wrong items or colors, resulting in customer dissatisfaction and high return rates. Furthermore, the time-intensive creation of 3D models for each product hindered efficiency.
Leveraging NVIDIA's powerful software suite, which includes TensorRT for high-speed inference and Omniverse for synthetic dataset creation and 3D model generation, in conjunction with cutting-edge hardware such as the NVIDIA Jetson Xavier NX GPU and Siemens IPC 520A, we implemented AI models, including the AI Visual Inspection Kit by Data Monsters. These models enable real-time order accuracy checks, irrespective of barcode information.
Project Highlights
In just four months, our project delivered a transformative solution. It not only ensures the recognition of goods without relying solely on barcode information but also automatically generates 3D models of items. The outcome? An impressive improvement in order accuracy, resulting in a staggering 90% reduction in returns, as well as a 30% acceleration in new product listings.
Siemens IPC 520A TensorBox
Siemens IPC 520A TensorBox
NVIDIA Jetson Xavier NX GPU
NVIDIA Jetson Xavier NX GPU

Leading Food and Beverage Manufacturer, Operating at Large Scale with Packaged Goods

Company C grappled with a persistent issue, a 3-5% defect ratio during the packaging process. This led to wastage and diminished customer satisfaction. The existing quality checks were conducted randomly, and the high-speed production line posed challenges for thorough inspection, resulting in undetected defects.
Leveraging the Siemens IPC 520A based on NVIDIA Jetson Xavier NX GPU, in addition to implementing AI models like the AI Visual Inspection Kit by Data Monsters, we designed a solution for real-time defect detection.
Project Highlights
Our intensive 4-month Proof of Concept (POC) project culminated in a fully operational prototype. This innovation excels in real-time defect identification and offers a game-changing solution. The system significantly reduces the defect ratio to a remarkable 70%, leading to substantial cost savings by minimizing waste and the need for rework.
Siemens IPC 520A TensorBox
Siemens IPC 520A TensorBox
NVIDIA Jetson Xavier NX GPU
NVIDIA Jetson Xavier NX GPU

Oil & Gas Industry, AI-Enhanced Pump Optimization and Predictive Maintenance

Critical to Company C's operations, its pumps undergo regular testing via real-time vibration analysis, infrared imaging, and visual inspections to prolong their lifespan and enhance productivity. While these methods offer valuable insights into current pump conditions, the engineering team grapples with automating capacity adjustments and accurately forecasting potential breakdowns. This challenge poses significant hurdles as it hampers their ability to preemptively address issues, leading to considerable downtime and financial losses.
The solution harnesses the power of NVIDIA H100 SXM5 GPUs for intricate real-time analytics, training, and predictive modeling, complemented by the Jetson Orin for robust edge computing. By integrating advanced AI algorithms, the system is finely tuned to measure and analyze vital pump metrics like vibration, flow rate, pressure, temperature across diverse components, speed, and motor power consumption. The system autonomously configures optimal flow rates, pressure, and speed, while accurately predicting potential breakdowns.
Project Highlights
Built within a few months, the AI system prototype enhances pump efficiency and reduces downtimes. The AI optimizes pump RPMs, Ramp-up, Ramp-down, impeller diameter and pressure based on real-time data, ensuring seamless operation and extending the pump's lifespan. Crucially, the system's predictive analytics anticipates potential breakdowns, enabling proactive maintenance. This strategic approach decreased maintenance costs and significantly improved operational stability, leading to substantial cost savings.
Jetson Orin
Jetson Orin

Robotics: AI-Enhanced Efficiency and Accuracy at Production Line

"In Company R's production line, robotic picking systems encounter obstacles due to the diverse properties of objects handled, ranging from varying weights, textures, to different orientations. The engineering team conducts routine tests involving visual inspections to assess and readjust the robots for diverse tasks. However, the absence of automated, real-time adaptability within the robotic systems results in inefficiencies, elevated error rates, and potential production delays. These issues directly impact the company's throughput and operational costs, posing significant challenges to seamless production.
Company R implemented an AI Visual Inspection Kit empowered by a Siemens IPC 520A, running on the potent NVIDIA Jetson Xavier NX GPU, seamlessly connected to Teledyne GigE cameras. This cutting-edge solution enables on-edge data collection and computation while leveraging TensorBox-optimized computer vision models. These models empower our robots with the remarkable ability to 'see' and dynamically adapt to the diverse range of products within our production line. The AI algorithms facilitate the robots' ability to self-adjust to different object characteristics, enhancing the picking process's speed and accuracy.
Project Highlights
Within a concise span of 4 months, the deployment of the AI Visual Inspection Kit onto our production line resulted in remarkable advancements. The AI-enabled robots showcased a heightened proficiency in accurately picking a diverse range of objects, leading to a pronounced reduction in errors and downtime. The system's real-time processing capabilities enabled instantaneous adjustments to the picking process, eliminating the necessity for manual recalibrations. As a result, company R reaps substantial cost savings and solidifies a robust competitive edge in the market, setting a new standard for efficiency and accuracy in our production endeavors.
Siemens IPC 520A TensorBox
Siemens IPC 520A TensorBox
Teledyne GigE cameras

Manufacturing Industry

Precision in manual and automated component installation is paramount for Company D, a leading European automotive concern. However, the ever-fluctuating market demands and lean manufacturing practices often lead to workstation imbalances and sudden peaks in assembly activities. These challenges have resulted in instances of incorrectly installed components during the assembly process. The reliance on traditional quality control methods involving manual inspection proves to be labor-intensive and prone to human error, particularly amidst high-volume production pressures. Consequently, delayed defect identification increases wastage and escalates rectification costs. Additionally, the manual checks create bottlenecks, hampering the overall efficiency of the assembly process and needlessly extending cycle times.
To combat challenges and elevate efficiency, Company D embraced an AI-driven solution aimed at automating component assembly verification. By harnessing the prowess of computer vision integrated with deep learning models, the system adeptly identifies improperly assembled components. Strategically positioned control cameras, each stationed along the assembly line and powered by NVIDIA Jetson Orin modules for edge AI processing, offer immediate validation, real-time analysis, and prompt feedback at every stage of the assembly process. This seamless AI integration enables accurate component verification, drastically reducing the need for manual checks and significantly mitigating errors and losses.
Project Highlights
After implementing the AI verification system, the company witnessed a remarkable enhancement in the precision of component installations. The substantial reduction in the necessity for manual quality checks streamlined the assembly process significantly. Early detection of assembly errors empowered immediate corrective actions, effectively curbing waste and preventing the costly repercussions of defective products advancing to later production stages or entering the market. Embracing a proactive approach to quality control through the AI system translated into heightened product reliability and increased customer satisfaction, ultimately fortifying the company's position within the market.
Jetson Orin
Jetson Orin

Machinery Industry

Within the machinery industry, the precision of harness assembly stands as a critical factor. Assemblers bear the responsibility of guaranteeing the accurate attachment of connectors, the presence of wiring shielding, and precise length measurements. However, manual verification processes tend to consume valuable time, often causing production bottlenecks and heightening the probability of errors. These challenges significantly contribute to inefficiencies, escalating rework rates, and inflating operational costs, consequently affecting Company Y's productivity and bottom line.
In tackling assembly challenges, Company D adopted an AI-powered Harness Assembly Quality Assurance system. This innovative solution integrates Siemens IPC 520A, NVIDIA Jetson Xavier NX GPU, and Teledyne GigE cameras stationed at individual workstations, enabling real-time monitoring of harness assembly. Leveraging TensorBox-optimized computer vision in tandem with SIMATIC EDGE, the system adeptly detects subtle deviations, offering immediate feedback. AI algorithms efficiently flag discrepancies, guaranteeing precise and specification-compliant assembly processes.
Project Highlights
After deploying the AI Quality Assurance system, the company observed remarkable improvements in harness assembly accuracy within a concise four-month period. Substantial reductions in error rates were achieved as the AI system offered real-time guidance, diminishing the necessity for manual inspections and subsequent rework. Consequently, the production process underwent a significant streamlining, exhibiting a noteworthy increase in throughput and a reduction in waste. The investment in AI technology proved highly beneficial, not only amplifying operational efficiency but also curbing costs linked to quality issues. This strategic advancement has positioned the company at the forefront of technological innovation within the machinery industry, granting a notable competitive edge in the market.
Siemens IPC 520A TensorBox
Siemens IPC 520A TensorBox
NVIDIA Jetson Xavier NX GPU
NVIDIA Jetson Xavier NX GPU
Teledyne GigE cameras

Join Our 4-Month Incubation Program for Maximum ROI!

November 15, 10 am PST

Online, Zoom

By Joining the AI Incubator you will be able to accelerate the development of your AI-powered system by:

Creating your Market Ready Solutions - Comprehensive codebase and AI models

Working on your specific business cases with measurable ROI

Preparing structured investment cases and providing investment support

We created an ecosystem to help you boost measurable business success avoiding common AI pitfalls

Faster results in
weeks vs. years
No need to hire experts for very advanced AI
Real-world corporate business cases with measurable ROI
Building AI reputation, corporate alignment and buy-in for projects
Structured timeframe and scalable delivery framework from PoC to production
AI Incubator Ecosystem Image

More about the 

AI Incubator 

At the heart of the AI Incubator lies a collaborative network of certified Elite NVIDIA ecosystem partners, united in the pursuit of innovation. These distinguished organizations bring a wealth of experience, boasting highly skilled teams with a proven track record in delivering exceptional NVIDIA ecosystem solutions, validated through years of successful practice and NVIDIA certification.

Within the incubator, these certified NVIDIA ecosystem partners join forces with industry-leading professionals from both NVIDIA and SIEMENS, working together to address the challenges faced by various companies. Moreover, subject matter experts and business specialists from client companies actively engage in this dynamic environment.

The AI Incubator harnesses the collective expertise of engineering firms and automation solution providers, enriching the incubator's projects with practical application and integration knowledge in the field of AI solutions.

Capital partners & investment support

Each project within the AI Incubator undergoes a rigorous evaluation process, designed to guarantee transparent and expeditious investment support. We are proud to have the support of prominent investment and financial institutions within the NVIDIA and Siemens ecosystems, ensuring substantial financial backing to propel innovation and achievement.

Our Funding Partners Include:

  • NVIDIA Inception
  • NVIDIA GPU Ventures
  • Next47 (Siemens Group)
  • Siemens Financial Services (SFS)

These esteemed partners stand ready to provide the necessary financial resources to help turn groundbreaking ideas into reality.

NVIDIA Technologies


  • Omniverse (USD, Replicator, Isaac SIM, Drive SIM, ACE)
  • Metropolis
  • NeMo
  • Riva
  • Maxine
  • Triton


  • RTX
  • DGX
  • IGX, incl. Jetson Orin


Our Funding Partners Include:

  • GPU-based Industrial Computers
  • Siemens Industrial Edge Platform

Meet our top industry experts from Siemens, NVIDIA and NVIDIA Elite partners

Solution architects, engineers, subject matter experts
452 Total headcount of experts
A collective 84 years in AI expertise
AI Incubator Team
AI Incubator Team


Business Development - NVIDIA Ecosystem, Siemens

Industrial AI solution architect and engineer. German’s background is in automotive manufacturing, manufacturing automation, supply chain management, AI. For the past 2 years he worked at Data Monsters as Solutions Architect focusing on NVIDIA Metropolis / DeepStream / TAO/ TensorRT / Triton, NVIDIA Omniverse, edge AI deployment and orchestration: NVIDIA FleetCommand.

AI Incubator Team


Director Product Management & Marketing Siemens Factory Automation

Raithel has an engineering degree (Dipl-Ing(FH)) from the TU Nürnberg (Germany) and has 27 years of experience in automation in various roles in R&D, Engineering, Product Management, and Marketing. Before moving to the USA, he has been with Siemens for more than 17 years, defining the next-generation automation systems and expanding Siemens’ Industrial PC portfolio to the IoT space. In the US, he focuses on integrating new technologies such as Edge and AI in Siemens Automation portfolio.

Thorsten Julich AI Incubator Team


Sr. Business Development Manager at Siemens | AI & Edge Computing

With over 20 years of experience in the automation industry, Thorsten Julich is a seasoned and passionate Sr. Business Development Manager at Siemens, where he lead the AI & Edge Computing, IPC and SCADA / HMI Software business in the US. His main focus is on large OEMs and end-users in discrete automation markets, such as automotive, oil and gas, renewable energy, food and beverage, and pharmaceuticals, as well as emerging industries.


CEO & Founder, TCL

Ramon has an engineering degree and 32+ years of experience in engineering, sales, marketing and supply chain management. Ramon started his career at Hewlett-Packard and held several executive positions at British Telecom, Sony Corporation, SoftBank Group and Accenture. Ever since he wrote his first line of code at the age of 11, Ramon has been fascinated by technology and its uses in support of corporate and societal goals.

AI Incubator Team


Advisor at AI Incubator

Caleb Eastman is a dynamic force, combining a background in business bootstrapping and a proven track record as the former Head of Product for a Silicon Valley venture-backed startup. With a strong presence in both Fortune 500 corporations and innovative startups throughout North America, Caleb is a trusted advisor. A systems engineer at heart and a prolific inventor, Caleb’s driving passion is exploring how cutting-edge technologies can synergize to bring meaningful change to our world. His High-Context Product Management™ framework accelerates product launches and shapes the future of innovation.


Advisor at AI Incubator

Adam Spunberg has worked for 15 years now in various roles centered around technology, from start-ups to major sports leagues, agencies, and most recently a Fortune 100-level CPG company (Anheuser-Busch InBev). He has led award-winning tech programs and pioneered AI and digital innovations across multiple regions and platforms. Most recently, he led generative AI efforts within AB InBev’s Supply Chain and delivered a portfolio of multiple rollouts and millions of dollars in KPI benefits.

Dotan AI Incubator Team


AI ethics advisor, researcher, speaker, 
and content creator

Ravit Dotan, PhD is an AI ethics advisor, researcher, speaker, and content creator. Her specialty is helping tech companies, investors, and procurement professionals develop responsible AI approaches. Ravit’s recognition includes a PhD in philosophy from UC Berkeley, being named one of the “100 Brilliant Women in AI Ethics” by Women in AI Ethics, being a finalist for the “Responsible AI Leader of the Year” Award by Women in AI, and frequent interviews in publications such as the New York Times, The Financial Times, CNBC, and TechCrunch.

How it works

In 2023, we will be collaborating with ten projects as part of our AI incubator program


Our ecosystem brings a wealth of experience, demonstrated by

  • Access to 102 world-class AI experts with domain expertise
  • Elite pool of 50 partners, experts, and architects
  • A collective 84 years in AI expertise
Industry recognition and PR Support 
Over 1,021 completed projects from leaders
Maintaining IP ownership
Pre-vet and validation of projects
  • Proven Strategies to reduce AI CapEx/OpEx
  • Minimizing risks (reputation, resources)
  • Real learnings across all projects / use cases

AI Incubator Partners offer a comprehensive range of support, including


Skilled professionals such as solution architects, engineers, subject matter experts, and business specialists


Hardware resources essential for model training and inference


Provision of necessary software licenses to facilitate the development process

The AI Incubator operates on-site, centrally located in the heart of Silicon Valley

Milestone events and workshops take place at two prestigious venues: the NVIDIA Headquarters in Santa Clara, CA, and the Siemens Factory Automation showroom in Campbell, CA. For day-to-day activities, the teams are based in a dedicated space in Sunnyvale, CA, providing a conducive environment for their innovative work.


NVIDIA Headquarters in Santa Clara, CA


Siemens Factory Automation showroom in Campbell, CA

Winter batch applications are open!