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Wednesday,  Sep 27
10:00 am PDT
Online, Zoom

Empowering Your Product with Voice Interface: A.Hands-On NVIDIA RIVA Workshop

About The Workshop

Join us for an immersive workshop, where you’ll learn how to unleash the potential of your product by incorporating a voice interface using NVIDIA RIVA. This interactive session will guide you through the process of voice-enabling using NVIDIA Riva, a GPU-accelerated speech AI—automatic speech recognition (ASR) and text-to-speech (TTS)—SDK for building fully customizable, real-time conversational AI pipelines and provide you with the knowledge, skills, and practical experience needed to successfully voice-enable your offerings.

Familiarize yourself with NVIDIA Riva
Evaluate the business value that can be derived from using NVIDIA Riva
Gain practical experience by working on various use cases to comprehend its functionality
Set realistic expectations for the project
Seek clarifications by asking questions
Plan the project structure in advance
Assess the costs and resources required for the project
Take measures to avoid any potential problems
Identify any potential risks associated with the project
Through out the workshop, you will be focusing on your individual case

Agenda and

10 mins

Introductions, goals, agenda

  • Get acquainted with fellow product managers and instructors;
  • Discuss workshop objectives and what you can expect to learn;
  • Outline the agenda for the session.
5 mins

Understanding the Need for NVIDIA Riva

  • Explore why incorporating NVIDIA RIVA is essential for product managers;
  • Understand the benefits and potential impact on user experience and product success.
10 mins

Interactive Part 1: Use Cases Overview and Exploration

  • Dive into various use cases where NVIDIA Riva can be implemented;
  • Gain insights into how voice interfaces can enhance product functionality and user interaction.
10 mins

Interactive Part 2: Exploring Attendees’ Real Use Cases

  • Share and discuss real use cases brought by the workshop attendees;
  • Analyze how NVIDIA RIVA can be applied to their specific product scenarios.
5 mins

Interactive Part 3: Use Case Presentation

Participants present their use cases to the group, highlighting the potential benefits of integrating NVIDIA Riva.

5 mins

Riva Implementation Process

  • Learn about the step-by-step process of implementing NVIDIA Riva;
  • Understand the key considerations, best practices, and potential challenges involved.
5 mins

Riva Workshop Feedback

  • Provide feedback on the workshop content, format, and overall experience;
  • Share any additional questions or areas that require clarification.
5 mins

Wrapping Up

  • Summarize key takeaways from the workshop;
  • Recap the importance of voice interface and NVIDIA RIVA for product managers.
Implementation process checklist
Two examples
Sample architectures

Our speakers


Data product manager / NLP solution architect

Ph.D. in Data Science. For the last four years with Data Monsters, I am responsible for launching, growing, and developing complex, knowledge-intensive IT products that use Data Science and Machine Learning technologies.

Artemy Malkov, PhD

CEO & Founder Data Monsters

Artificial Intelligence and Machine Learning consultant and the CEO of Data Monsters since 2008. Deep understanding of complex systems, business analysis, applied research, nonlinear dynamics, statistical distributions, and ML/AI applications to retail, manufacturing, healthcare, advertising, document processing, conversational and recommender systems.

Tripti Singhal

Expert from NVIDIA

Tripti Singhal is a Senior Solutions Architect on the NVIDIA Partner Network team in the Worldwide Field Organization at NVIDIA focusing on Conversational AI. She has been at NVIDIA for six years and received her bachelor's degree in Computer Science at University of California, Santa Barbara.

Zhansaya Zhapar

ASR Solutions Consultant | Data Monsters

Riva technologies specialist responsible for the complete pipeline, from gathering data to deploying fine-tuned models. With a focus on ASR, accomplished multiple projects for languages, including Italian, Spanish, English, and diverse accents.

Max Pavlov

Head of Project Office

Building a bridge between AI technologies and business needs. Putting AI into production.

Dan Lesovodski

Partner, Data Monsters

Managed 46 AI projects for large companies, including GE, Intel, AB InBev, and Boston Scientific. Author of the course “AI for managers” on Coursera.

Dennis Khvostionov

Experienced entrepreneur and Chief Technology Officer

His expertise lies in the area of data science. Presently, he serves as the CTO for both Data Monsters, an AI company, and TopHap, a platform dedicated to real estate analytics, mapping, and data visualization. Before these roles, Dennis worked as the CTO of DGLogik, leading up to its acquisition by Acuity Brands in 2016. There, he developed practical tools for IoT data integration and visualization. He firmly believes in the value of data and focuses on creating tools to highlight the patterns within.


NVIDIA is the leading provider of GPUs for AI, and scientific research

An NVIDIA Elite service delivery partner with a portfolio of 100+ AI projects.

This hands-on workshop will help you procure and commission an AI system for industrial quality inspections:
During this session, you will work on your own case. The workshop will be held by industrial AI experts from leading tech companies.
Agenda and timing - 60 mins
Introduction - 5 mins
Use case estimations & budget and risk assessment
- 15 mins
Participants will use Data Monsters’ framework to structure their use cases and required resources. Data volume, throughput, and storage strategies (time to store & fast and long-term storage). Develop solution architecture and determine integration strategies.

Business case evaluation. Relation of AI accuracy and business value
- 10 mins
We will use a spreadsheet to evaluate the business effect basing on a participant’s use cases.

How to choose a system. Evaluation parameters
- 15 mins
Requirements, expectations, and the right questions to ask. Participants and experts will elaborate the key features that define success or failure.

Project structure. AI system commissioning - 5 mins
Project structure framework: POC, Pilot, and Production phases. The ins and outs, what to expect, and how to avoid pitfalls. Common mistake at commissioning - overfitting, and train\test mismatches. Your expert team roles.

Next steps - 5 mins

Q&A section - 5 mins
This practical session will help you to:
Establish and clarify your understanding of AI core concepts,
Learn about best AI use-cases in your industry, 
Understand what 5 areas should be managed within an AI project,
Set up your next actions towards your goal. 
During the session, we will cover 8 steps and topics:
“What is AI?”, “How does AI work?, and “What can and can't AI do?”
The most popular AI use cases in manufacturing.
How to spot a feasible and valuable AI use-case that relates to your needs?
How to estimate AI projects and evaluate ROI? The cost structure.
Assessment, PoC, Pilot - The major phases of an AI project’s life cycle.
What can go wrong? The main risks in AI projects.
Success or failure? Terminate or continue? Setting the right acceptance criteria.
Scaling challenges. How to go beyond a PoC?
Who can benefit from this session?
If you're a manager or director striving to make the most out of AI, and you work in one of these industries:
Automotive Manufacturing
Food & Beverages
Electronics & Semiconductors
Logistics & Supply Chain
Innovations, Operations, Quality Management, Executives, Product managers, Solution Architects, Project Managers, Chief Data Officer, CTO
What you get:
Use cases
AI building blocks
Best practices in AI project managementand understanding of how to deal with:
 - Practical AI implementation
 - AI team roles & expectations
 - Investment in AI: risks, deliverables, expenses
 - How to measure success
Use cases
AI building blocks
Best practices in AI project managementand understanding of how to deal with:
 - Practical AI implementation
 - AI team roles & expectations
 - Investment in AI: risks, deliverables, expenses
 - How to measure success
Russ Sagert
Director Business Development - Industrial Manufacturing / IoT, NetApp
An expert in developing and bringing to market Digital Transformation solutions for manufacturing plant operators across the oil and gas, mining, power utilities, automotive, and high-tech fabrication industries.
DJ Bush
Global Client Executive - HPC/AI/ML, Sycomp
A global client executive working closely on integrating AI/ML solutions across different industries.
Piyush Modi
Business Development of Industrial Sector, NVIDIA
Responsible for global business development and strategy for the industrial sector at NVIDIA. Over the past 20 years, he has held the positions of CTO, Senior VP, and Head of Research Labs at various companies.
Dan Lesovodski
Partner, Data Monsters
Managed 46 AI projects for large companies, including GE, Intel, AB InBev, and Boston Scientific. Author of the course “AI for managers” on Coursera.
German Suvorov
Head of Industrial AI, Data Monsters

An expert in AI for industrial applications with over 20 years of experience in automotive manufacturing, advanced materials engineering, industrial automation, supply chain management, and information technologies.

NetApp is a global leader in data management solutions, providing a common infrastructure for moving data from edge to core to cloud.  They provide a simplified approach to managing data and accelerating applications whether on-premise, in the cloud, or both.

Sycomp is a global system integrator, developing architectures that bring together data science, software and infrastructure to provide clients with a holistic approach to deploying AI/ML solutions.  With their global footprint of over 40 countries, they bring a level of standardization to global technology deployments.

Data Monsters. An NVIDIA Elite service delivery partner with a portfolio of 100+ AI projects.