Enterprise AI | Kisaco Research

Enterprise AI

Enterprise AI

As AI evolves into agentic systems where dozens to hundreds of LLMs and specialized models work in concert, running them efficiently in data centers poses immense software challenges. From disaggregating massive LLMs and aggregating smaller models to dynamically scheduling diverse and unpredictable user requests, every layer requires precise optimization. Inference workloads must navigate continuous growth and rapid innovation, pushing the limits of conventional software stacks. Just as DeepSeek redefined its entire infrastructure beyond CUDA, Moreh is partnering with leading LLM players to deliver the fastest, most advanced distributed inference framework on AMD and Tenstorrent.  

Optimized Infrastructure
Inferencing

Author:

Gangwon Jo

CEO
Moreh

Gangwon Jo is the co-founder and CEO of Moreh Inc., a startup funded by AMD that develops optimized infrastructure software, enabling more efficient and flexible AI infrastructure at scale. Moreh’s software supports AI workloads on AMD as well as other accelerator platforms, such as Tenstorrent.

Gangwon was the chief architect of “Chundoong,” a supercomputer built using AMD consumer GPUs, which was recognized as one of the world’s TOP500 supercomputers in 2012.

In 2022, Gangwon was named one of MIT Technology Review’s “Innovators Under 35.” He holds a Ph.D. in Electrical and Computer Engineering from Seoul National University.

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Gangwon Jo

CEO
Moreh

Gangwon Jo is the co-founder and CEO of Moreh Inc., a startup funded by AMD that develops optimized infrastructure software, enabling more efficient and flexible AI infrastructure at scale. Moreh’s software supports AI workloads on AMD as well as other accelerator platforms, such as Tenstorrent.

Gangwon was the chief architect of “Chundoong,” a supercomputer built using AMD consumer GPUs, which was recognized as one of the world’s TOP500 supercomputers in 2012.

In 2022, Gangwon was named one of MIT Technology Review’s “Innovators Under 35.” He holds a Ph.D. in Electrical and Computer Engineering from Seoul National University.

As AI adoption accelerates, securing sensitive data during inference has become a critical challenge, particularly in regulated and privacy-sensitive environments. Fully Homomorphic Encryption (FHE) enables computation on encrypted data without ever exposing the underlying information, making it a breakthrough for secure, private LLM deployments. This session explores how FHE can be practically applied to scale large language models (LLMs) while maintaining strict data confidentiality. Dr. Walden "Wally" Rhines will cover recent advancements, performance innovations, and real-world use cases demonstrating how FHE unlocks scalable, privacy-preserving AI.

Data Privacy & Governance

Author:

Dr. Walden “Wally” Rhines

Board of Directors
Cornami

WALDEN C. RHINES is President & CEO of Cornami. He is also CEO Emeritus of Mentor, a Siemens business, focusing on external communications and customer relations. He was previously CEO of Mentor Graphics for 23 years and Chairman of the Board for 17 years. During his tenure at Mentor, revenue nearly quadrupled and market value of the company increased 10X.

Prior to joining Mentor Graphics, Dr. Rhines was Executive Vice President, Semiconductor Group, responsible for TI’s worldwide semiconductor business. During his 21 years at TI, he was President of the Data Systems Group and held numerous other semiconductor executive management positions.

Dr. Rhines has served on the boards of Cirrus Logic, QORVO, TriQuint Semiconductor, Global Logic and as Chairman of the Electronic Design Automation Consortium (five two-year terms) and is currently a director. He is also a board member of the Semiconductor Research Corporation and First Growth Children & Family Charities. He is a Lifetime Fellow of the IEEE and has served on the Board of Trustees of Lewis and Clark College, the National Advisory Board of the University of Michigan and Industrial Committees advising Stanford University and the University of Florida.

Dr. Rhines holds a Bachelor of Science degree in engineering from the University of Michigan, a Master of Science and PhD in materials science and engineering from Stanford University, a master of Business Administration from Southern Methodist University and Honorary Doctor of Technology degrees from the University of Florida and Nottingham Trent University.

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Dr. Walden “Wally” Rhines

Board of Directors
Cornami

WALDEN C. RHINES is President & CEO of Cornami. He is also CEO Emeritus of Mentor, a Siemens business, focusing on external communications and customer relations. He was previously CEO of Mentor Graphics for 23 years and Chairman of the Board for 17 years. During his tenure at Mentor, revenue nearly quadrupled and market value of the company increased 10X.

Prior to joining Mentor Graphics, Dr. Rhines was Executive Vice President, Semiconductor Group, responsible for TI’s worldwide semiconductor business. During his 21 years at TI, he was President of the Data Systems Group and held numerous other semiconductor executive management positions.

Dr. Rhines has served on the boards of Cirrus Logic, QORVO, TriQuint Semiconductor, Global Logic and as Chairman of the Electronic Design Automation Consortium (five two-year terms) and is currently a director. He is also a board member of the Semiconductor Research Corporation and First Growth Children & Family Charities. He is a Lifetime Fellow of the IEEE and has served on the Board of Trustees of Lewis and Clark College, the National Advisory Board of the University of Michigan and Industrial Committees advising Stanford University and the University of Florida.

Dr. Rhines holds a Bachelor of Science degree in engineering from the University of Michigan, a Master of Science and PhD in materials science and engineering from Stanford University, a master of Business Administration from Southern Methodist University and Honorary Doctor of Technology degrees from the University of Florida and Nottingham Trent University.

Software Infra

Author:

Aswini Atibudhi

Distinguished Architect
Walmart

Aswini is a Distinguished Architect at Walmart Global Tech, with over 22 years of IT experience in designing scalable AI/ML, micro frontend, microservices, and cloud applications. His professional expertise encompasses diverse domains including  e-commerce, finance, telecom and healthcare meticulously developed through his tenure at Walmart, Cisco, Equinix, Finastra, and TCS. Over seven years at Walmart, he has been a founding member of critical platforms like Last Mile Delivery, Fleet Management, MerchOne, Supplier Portal and several others. As a recognized expert in generative AI, Aswini specializes in leveraging machine learning and large language models to create transformative digital experiences, including personalized content generation and AI-driven customer engagement.

He has received numerous awards including Walmart’s Innovation Award, Equinix’s Top Performer Award, and Cisco’s Group Race Award. With many certifications in AI, machine learning, and cloud technologies, he stays at the forefront of innovation. Known for his strategic insights, Aswini has a proven ability to deliver transformative AI solutions across industries. 

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Aswini Atibudhi

Distinguished Architect
Walmart

Aswini is a Distinguished Architect at Walmart Global Tech, with over 22 years of IT experience in designing scalable AI/ML, micro frontend, microservices, and cloud applications. His professional expertise encompasses diverse domains including  e-commerce, finance, telecom and healthcare meticulously developed through his tenure at Walmart, Cisco, Equinix, Finastra, and TCS. Over seven years at Walmart, he has been a founding member of critical platforms like Last Mile Delivery, Fleet Management, MerchOne, Supplier Portal and several others. As a recognized expert in generative AI, Aswini specializes in leveraging machine learning and large language models to create transformative digital experiences, including personalized content generation and AI-driven customer engagement.

He has received numerous awards including Walmart’s Innovation Award, Equinix’s Top Performer Award, and Cisco’s Group Race Award. With many certifications in AI, machine learning, and cloud technologies, he stays at the forefront of innovation. Known for his strategic insights, Aswini has a proven ability to deliver transformative AI solutions across industries. 

As AI infrastructure outgrows tightly coupled systems, we’re witnessing a shift toward openness and modularity in designing full-stack solutions for AI. In this session, we’ll examine the rise of Software-Driven Fabrics (SDF) , a programmable, vendor-neutral control plane for modern AI networking. SDF makes real-time data coordination across heterogeneous accelerators and fabrics possible, offering a new, democratized model for GPU scalability and network resiliency.

Software Infra

Author:

Prashanth Thinakaran

Distinguished AI Infrastructure Engineer
Clockwork Systems

Prashanth Thinakaran is a Distinguished AI Infrastructure Engineer at Clockwork Systems, a pioneer in nano-second precise network telemetry and software-driven resilience that addresses the unprecedented scale, performance, and reliability Modern AI workloads demand from GPU clusters. In this role, he partners with AI Infrastructure teams at enterprises, hyperscalers and neoclouds to increase their visibility into issues impacting cluster uptime and optimize their availability and utilization with Clockwork’s solution. 

Previously, he helped AI-native companies build on cloud-based GPU platforms, providing deep technical guidance on distributed training and inference, multi-node scaling, and performance tuning across complex infrastructure stacks. His Neocloud experience bridged the gap between product engineering and customer enablement, helping fast-moving teams adopt best practices in massive-scale model deployment and operations. Prior to that, Prashanth played a pivotal role at Cerebras Systems -  a market leader in high-speed inferencing, - in the design, and deployment of Condor Galaxy 1, a Wafer-scale supercomputer. His work enabled rapid deployment timelines and seamless scaling of AI infrastructure across globally distributed data centers designed for both Inference and Training.

Prashanth also holds a Ph.D. in Computer Science and Engineering from Penn State, where his research focused on high-performance computing and cloud systems. His academic work has been published in top-tier venues including USENIX NSDI, ACM Middleware, ICDCS, and ACM SoCC. He has authored over a dozen peer-reviewed papers and a book chapter, and served as a reviewer for journals such as IEEE TPDS and TCC. During his Ph.D., he held teaching roles in systems programming, and computer architecture, and collaborated with Intel, VMware, and Adobe Research through internships, solving systems challenges at the intersection of academia and industry.



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Prashanth Thinakaran

Distinguished AI Infrastructure Engineer
Clockwork Systems

Prashanth Thinakaran is a Distinguished AI Infrastructure Engineer at Clockwork Systems, a pioneer in nano-second precise network telemetry and software-driven resilience that addresses the unprecedented scale, performance, and reliability Modern AI workloads demand from GPU clusters. In this role, he partners with AI Infrastructure teams at enterprises, hyperscalers and neoclouds to increase their visibility into issues impacting cluster uptime and optimize their availability and utilization with Clockwork’s solution. 

Previously, he helped AI-native companies build on cloud-based GPU platforms, providing deep technical guidance on distributed training and inference, multi-node scaling, and performance tuning across complex infrastructure stacks. His Neocloud experience bridged the gap between product engineering and customer enablement, helping fast-moving teams adopt best practices in massive-scale model deployment and operations. Prior to that, Prashanth played a pivotal role at Cerebras Systems -  a market leader in high-speed inferencing, - in the design, and deployment of Condor Galaxy 1, a Wafer-scale supercomputer. His work enabled rapid deployment timelines and seamless scaling of AI infrastructure across globally distributed data centers designed for both Inference and Training.

Prashanth also holds a Ph.D. in Computer Science and Engineering from Penn State, where his research focused on high-performance computing and cloud systems. His academic work has been published in top-tier venues including USENIX NSDI, ACM Middleware, ICDCS, and ACM SoCC. He has authored over a dozen peer-reviewed papers and a book chapter, and served as a reviewer for journals such as IEEE TPDS and TCC. During his Ph.D., he held teaching roles in systems programming, and computer architecture, and collaborated with Intel, VMware, and Adobe Research through internships, solving systems challenges at the intersection of academia and industry.



Optimized Infrastructure
Gen AI
Agentic AI

Author:

Jeongkyu Shin

CEO
Lablup

Jeongkyu Shin is the founder of Lablup Inc. and has made significant contributions to open-source projects over the past two decades, including his lead developer role in the Textcube Project. He has served as an AI expert at Google Developers Experts since 2017 and was active in the Innovative Steering Board of the Northeast Asia Open Source Software Promotion Forum until 2022. In recognition of his contributions to the technology industry, he was awarded the prestigious Industrial Service Medal by the Korean government in 2024. Additionally, Jeongkyu supports startup companies as a technical mentor at Google for Startups Accelerator.

He holds a Ph.D. in Statistical Physics from POSTECH, where his research focused on complex systems, agent-based models, and computational neuroscience. Throughout his career, Jeongkyu has led machine learning and open-source projects in various companies and labs, specializing in text classification, entropy-related information compression, and contextual search. Since 2015, he has been developing Backend.AI, an open-source, hyper-scalable AI infrastructure platform (available at https://www.backend.ai).

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Jeongkyu Shin

CEO
Lablup

Jeongkyu Shin is the founder of Lablup Inc. and has made significant contributions to open-source projects over the past two decades, including his lead developer role in the Textcube Project. He has served as an AI expert at Google Developers Experts since 2017 and was active in the Innovative Steering Board of the Northeast Asia Open Source Software Promotion Forum until 2022. In recognition of his contributions to the technology industry, he was awarded the prestigious Industrial Service Medal by the Korean government in 2024. Additionally, Jeongkyu supports startup companies as a technical mentor at Google for Startups Accelerator.

He holds a Ph.D. in Statistical Physics from POSTECH, where his research focused on complex systems, agent-based models, and computational neuroscience. Throughout his career, Jeongkyu has led machine learning and open-source projects in various companies and labs, specializing in text classification, entropy-related information compression, and contextual search. Since 2015, he has been developing Backend.AI, an open-source, hyper-scalable AI infrastructure platform (available at https://www.backend.ai).

Author:

Ankur Mehrotra

GM, SageMaker AI
AWS

Ankur Mehrotra is a GM at AWS Machine Learning and leads foundational SageMaker AI services such as SageMaker Studio, Notebooks, Training, Inference, Feature Store, MLOps, etc. Before SageMaker AI, he led AI services for personalization, forecasting, healthcare & life sciences, edge AI devices and SDKs, as well as thought leadership programs such as AWS DeepRacer. Ankur has worked at Amazon for over 15 years. Before joining AWS, he spent several years in Amazon’s Consumer organization, where he led the development of automated marketing/advertising systems, as well as automated pricing systems.

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Ankur Mehrotra

GM, SageMaker AI
AWS

Ankur Mehrotra is a GM at AWS Machine Learning and leads foundational SageMaker AI services such as SageMaker Studio, Notebooks, Training, Inference, Feature Store, MLOps, etc. Before SageMaker AI, he led AI services for personalization, forecasting, healthcare & life sciences, edge AI devices and SDKs, as well as thought leadership programs such as AWS DeepRacer. Ankur has worked at Amazon for over 15 years. Before joining AWS, he spent several years in Amazon’s Consumer organization, where he led the development of automated marketing/advertising systems, as well as automated pricing systems.

Author:

Sakshi Naik

Lead Data Scientist
Walgreens Boots Alliance

Sakshi Naik is an AI Consultant at Walgreens Boots Alliance, where she leads the development of ethical and impactful AI solutions in healthcare. With a Master’s in Computer Science from Stevens Institute of Technology and a Bachelor’s in IT Engineering from Mumbai University, she brings deep technical expertise across data science, machine learning, and AI infrastructure.

Sakshi is also a recognized voice in AI policy. She has advised U.S. Senators and Members of the House of Representatives on the future of responsible AI and serves as Secretary of the IEEE Connecticut Section. As a member of the IEEE AI Policy Committee (AIPC), she actively contributes to shaping national and global frameworks for trustworthy AI.

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Sakshi Naik

Lead Data Scientist
Walgreens Boots Alliance

Sakshi Naik is an AI Consultant at Walgreens Boots Alliance, where she leads the development of ethical and impactful AI solutions in healthcare. With a Master’s in Computer Science from Stevens Institute of Technology and a Bachelor’s in IT Engineering from Mumbai University, she brings deep technical expertise across data science, machine learning, and AI infrastructure.

Sakshi is also a recognized voice in AI policy. She has advised U.S. Senators and Members of the House of Representatives on the future of responsible AI and serves as Secretary of the IEEE Connecticut Section. As a member of the IEEE AI Policy Committee (AIPC), she actively contributes to shaping national and global frameworks for trustworthy AI.

Data Privacy & Governance
Enterprise Use Case

Author:

Anusha Nerella

Senior Principal Software Engineer
State Street

Anusha Nerella is an award-winning AI and fintech innovator known for her original contributions in transforming institutional trading and digital finance. She has pioneered AI-driven trading strategies, real-time big data systems, and automation frameworks that have redefined how financial institutions operate. Anusha’s innovations—from modernizing Barclaycard’s digital payments infrastructure during COVID-19 to architecting intelligent trading models—have driven measurable impact, earning her recognition as a thought leader shaping the future of AI-powered finance.

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Anusha Nerella

Senior Principal Software Engineer
State Street

Anusha Nerella is an award-winning AI and fintech innovator known for her original contributions in transforming institutional trading and digital finance. She has pioneered AI-driven trading strategies, real-time big data systems, and automation frameworks that have redefined how financial institutions operate. Anusha’s innovations—from modernizing Barclaycard’s digital payments infrastructure during COVID-19 to architecting intelligent trading models—have driven measurable impact, earning her recognition as a thought leader shaping the future of AI-powered finance.

Responsible AI is often framed in terms of ethical models and fair data—but the foundation for responsibility lies in infrastructure. In this talk, we’ll explore how platform-level capabilities like environment isolation, auditability, workload reproducibility, and resource-aware orchestration are essential to delivering AI that’s not just performant, but trustworthy. We’ll also examine how infrastructure decisions directly impact the quality and reliability of model evaluations—enabling teams to catch bias, ensure compliance, and meet evolving governance standards. If you’re building or scaling AI systems, this session will show how infrastructure becomes the enabler of responsible AI at every stage.

Data Privacy & Governance
Enterprise Use Case

Author:

Taylor Smith

Senior AI Advocate
Red Hat

Taylor Smith is a Senior AI Advocate at Red Hat, where she champions open source innovation and the responsible adoption of AI at scale. With a background in software development, Kubernetes, Linux, and technical partnerships, she focuses on helping organizations build and operationalize AI using modern infrastructure. Taylor is passionate about making AI more accessible, trustworthy, and grounded in real-world use cases. 

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Taylor Smith

Senior AI Advocate
Red Hat

Taylor Smith is a Senior AI Advocate at Red Hat, where she champions open source innovation and the responsible adoption of AI at scale. With a background in software development, Kubernetes, Linux, and technical partnerships, she focuses on helping organizations build and operationalize AI using modern infrastructure. Taylor is passionate about making AI more accessible, trustworthy, and grounded in real-world use cases. 

Data Privacy & Governance
Enterprise Use Case

Author:

Michael McLaughlin

Head of AI ML and Advanced Analytics
Children's National Hospital

Mike is the Head of AI/ML & Advanced Analytics at the Children’s National Hospital in Washington DC. At Children’s he leads the team responsible for developing, monitoring, and maintaining custom AI/ML applications in addition to driving AI governance and upskilling initiatives. He’s spent his entire career in the healthcare industry emphasizing AI and advanced analytics. His prior roles include leadership roles at Monogram Health, Exact Sciences, and Elevance.

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Michael McLaughlin

Head of AI ML and Advanced Analytics
Children's National Hospital

Mike is the Head of AI/ML & Advanced Analytics at the Children’s National Hospital in Washington DC. At Children’s he leads the team responsible for developing, monitoring, and maintaining custom AI/ML applications in addition to driving AI governance and upskilling initiatives. He’s spent his entire career in the healthcare industry emphasizing AI and advanced analytics. His prior roles include leadership roles at Monogram Health, Exact Sciences, and Elevance.