October 7 - 9, 2025

Call For Speakers Open

Renaissance Hotel Austin

October 7 - 9, 2025 | Austin, Texas

6th Annual MLOps World | GenAI Summit 2025

Call for speakers now open

The event that takes AI/ML & agentic systems from concept to large-scale production

3 Days • 16 Tracks • 75 Sessions • Vibrant Expo

Why attend: Optimize & Accelerate

Build optimal strategies

Learn emerging techniques and approaches shared by leading teams who are actively scaling ML, GenAI, and agents in production.

Increase project efficiency

Minimize project risks, delays, and missteps by learning from case studies that set new standards for impact, quality, and innovation.

Make better decisions

Make better, faster decisions with lessons and pro tips from the teams shaping ML, GenAI and Agenetic AI systems in production.

3 Days of Context, Insights, and Connections

Learn from leading minds, sharpen your skills, and connect with innovators driving safe and effective AI in the real world.

Pre-Event
  • Virtual Summit
  • Super Early Bird Event
Day 1
  • Summit:
    • Talks, Panels, & Workshops
  • Expo:
    • Lightning Talks
    • Brain Dates
    • Community Pitches
    • Startup Zone
    • Vendor Booths
  • Opening Party
Day 2
  • Keynote
  • Summit Day 2
  • Expo Day 2

Why attend: Connect & Grow

Grow industry influence

Join Brain Dates, Speaker’s Corner, Community Stage, or deliver a talk to share your expertise and amplify your industry impact.

Equip your team to win

Stay ahead of fast-moving competitors by giving your team the insights, skills, and contacts they need to exceed expectations.

Build career momentum

Make every hour count by using our event app to hyper-focus on the right topics and people who will help shape your future in AI.

2025 Summit: Full-Spectrum AI

The themes and tracks of our Summit are curated by AI practitioners. Detailed 2025 agenda coming soon.

2025 THEME: LLM Infrastructure & Operations

AI Infrastructure Strategy & Platform Engineering
This track covers the key architectural choices and infra strategies behind scaling AI and LLM systems in production—from bare metal to Kubernetes, GPU scheduling to inference optimization. Learn what it really takes to build and operate reliable GenAI and agent platforms at scale.

This 2025 track covers real-world patterns and pitfalls of running LLMs on Kubernetes. Topics include GPU scheduling, autoscaling, memory isolation, and managing cost and complexity at scale.

This 2025 track explores the realities of deploying ML in regulated, resource-constrained, or air-gapped environments. Talks focus on infrastructure design, data access, and managing tradeoffs when the cloud isn’t an option.

What does it mean to observe an LLM in production? This 2025 track unpacks logging, tracing, token-level inspection, and metrics that actually help teams debug and improve deployed models.

LLMs are changing how we think about data pipelines. This track examines the shifting roles of ETL, vector stores, and retrieval workflows in context-rich, model-driven systems.

Code has Git, ML has… a mess. This track dives into managing model, data, and pipeline versions in a reproducible, team-friendly way.
From Triton to ONNX to custom CUDA, this track explores how inference gets faster. Talks focus on low-level optimization, compilation, and maximizing performance on modern hardware.
This track dives into the performance, cost, and reliability challenges of running inference at scale. From token streaming to model compilation, caching strategies to hardware-aware scheduling, we’ll explore the systems and techniques that power fast, efficient, and production-ready AI inference.
This track focuses on building and scaling multimodal systems—models that handle text, image, audio, or video—in production. Learn how teams are designing serving stacks, data flows, and evaluation methods for real-world use.

2025 THEME: MLOps & Organizational Scale

AI Product Strategy & Delivery

AI Product Strategy & Delivery

This track covers how teams manage AI risk in production—through model governance, audit trails, compliance workflows, and strategies for monitoring model behavior over time.

Not every team has a platform squad or unlimited infra budget. This track shares practical approaches to shipping ML with lean teams—covering lightweight tooling, automation shortcuts, and lessons from teams doing more with less.

Coordination gets harder as teams and models scale. This track shares lessons on aligning workflows, managing shared infrastructure, and reducing friction across cross-functional ML teams.
Security doesn’t end at deployment. This track covers threat models, model hardening, data protection, and supply chain risks across the entire ML lifecycle.
Training isn’t just about epochs and GPUs. Talks focus on reproducibility, retraining triggers, pipeline automation, and how teams manage iterative experimentation at scale.

Good outcomes start with the right scope. Learn how teams are adapting scoping processes to account for LLMs, agents, and ambiguous project boundaries in fast-moving environments.

2025 THEME: AI Agents & Agentic Workforces

AI Agents for Developer Productivity

This track highlights practical uses of agents to streamline dev workflows—from debugging and code generation to test automation and CI/CD integration.

Agents can now assist in model testing, monitoring, and rollback decisions. The track focuses on how teams are using autonomous systems to harden their ML deployment workflows.

This track explores how teams are combining human oversight with semi-autonomous agents to scale support, operations, and decision-making across the business.

This 2025 track traces the design patterns shaping modern agents—from prompt engineering to tool use to memory and planning strategies. Real systems, not just frameworks.

Deploying agents is not the same as building them. This 2025 track focuses on the infrastructure, safety checks, and governance needed to run agents reliably in production.

VIEW 2024 AGENDA

Our Expo is where innovation, ideas, and connections come to life

Transform from attendee to active participant by leveling-up your professional contacts, exchanging ideas, and even grabbing the mic to share a passion project.

Make New Connections​

Connect with AI Practitioners

Transform from attendee to active participant by leveling-up your professional contacts, exchanging ideas, and even grabbing the mic to share a passion project.

Brain Dates

Arrange small-group meetups via the app to share insights, grow your network, and build career momentum.

Speakers' Corner

Take the mic to host your own session, share your expertise, and amplify your industry influence.

Vendor Booths

Community Pitches

Share your big idea and find partners who care, helping you shape better decisions and drive impact.

Startup Zone

Meet early-stage companies solving tomorrow’s challenges, offering fresh ideas to keep your team ahead.

Expo Expo Expo Expo Expo Expo Expo Expo Expo Expo Expo Expo

40+ Technical Workshops and Industry Case Studies

2024 Speakers

Note: The Call for Speakers for MLOps World | GenAI Summit 2025 is now open! Learn more

Shreya Rajpal

CEO & Co-Founder, Guardrails AI

Open-Ended and AI-Generating Algorithm in the Era of Foundation Models

Jeff Clune

Professor, University of British Columbia
Senior Research Advisor, DeepMind, 
AI Chair, CIFAR

Jepson Taylor

Former Chief ai strategist datarobot & dataiku

Dre Olgiati

Distinguished Engineer, AI/ML, LinkedIn

Anu Reddy

Senior Software Engineer, Google

Konstantin Gizdarski

Senior ML Software Engineer, Marketplace, Lyft

Maxime Labonne

Senior Staff Machine Learning Scientist, Liquid AI

Aishwarya Naresh Reganti

Applied Scientist, Amazon Web Services

VIEW ALL 2024 SPEAKERS

Latest News

Early Bird tickets are on sale now for the 6th annual MLOps World | GenAI Summit taking place October 8-9, 2025 at The Renaissance Austin. Join early to get maximum savings.

ON SALE: Early Bird Tickets For MLOps World | GenAI Summit 2025

TMLS Backstage: LLM Evals & Guardrails In Production

TMLS Backstage Live Podcast: What’s really happening in the world of agent tooling? Join Denys Linkov, Diego Oppenheimer, and Priyankya Somrah as they discuss insights from the Benchmark Report on Agentic Ops,  a first-of-its-kind look into how teams are actually building and deploying agentic systems.

TMLS Backstage: The State of Agents OPS

Presentation: Why Evaluation is the Missing Link in GenAI Product Success

Stack Session 03 (Free): Agents & Ops

Curated by AI Practitioners

All sessions and workshops have been hand-picked by a Steering Committee of fellow AI practitioners who obsess about delivering real-world value for attendees.

Denys Linkov

Event Co-Chair & Head of ML at WiseDocs

“We built this year’s summit around practical takeaways. Not theory but actual workflows, strategies, and the next three steps for your team. We didn’t want another ‘Intro to RAG’ talk. We wanted the things people are debugging, scaling, and fixing right now.”
MEET STEERING COMMITTEE

Volunteering

Apply for the opportunity to get exclusive behind the scenes access to the MLOps World experience while growing your network and skills in real-world artificial intelligence.

COMING SOON

Austin

Renaissance Austin Hotel

Once again our venue is the beautiful Renaissance Austin Hotel which delivers an exceptional 360 experience for attendees, complete with restaurants, rooftop bar, swimming pool, spa, exercise facilities, and nearby nature walks. Rooms fill up fast, so use our code (MLOPS25) for discounted rates.

GET ROOM DEAL

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Join our Monthly Newsletter to be first to get expert videos from our flagship events and community offers including the latest Stack Drops.

Join Summit Updates to learn about event-specific news like ticket promos and agenda updates as well invites to join our free online Stack Sessions.

Choose what works best for you and update your email preferences at any time.

Hear From Past Attendees

“If you want to hear from the experts, in real-time, and learn what's happening in the space - come here!”
Hugo Bowne-Anderson
Data and AI Scientist, Consultant, Podcaster
“I leave this type of event with with my head spinning with a lot of new ideas and hopefully other people do as well”
Joe ReisAcclaimed Author, CEO Ternary Data
“I can barely begin to explain how much your invite changed my life. Not only did I learn a TON at the conference but the knowledge I gained completely changed the trajectory of my career”
Scott Askinosie M.S. Ph.D.AI Developer
“It's the top event in the United States where you can get up to speed and learn about all things AI and Generative AI”
Marinela ProfiGlobal Market Lead for AI Agents and Generative AI, SAS

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Austin

Get Super Early Bird

We’ve put together our best package ever for early attendees. But don’t wait, this offer ends on July 11th:

  • Save 25% on tickets
  • Invitation to exclusive networking event
  • Limited edition Robo Cowboy baseball hat
  • Fist pick to claim special offers and perks

There’s also an additional 5% discount available for team purchases of 5 tickets or more.

FAQ

When and where is MLOps World?

MLOps World | GenAI Summit takes place Oct 7th (virtual) and then October 8-9 in person, at the beautiful Renaissance Hotel Austin, Located in the Arboretum

Address: 9721 Arboretum Blvd, Austin, TX 78759, United States

Yes, please contact [email protected] and we’ll send a prompt response.

Tickets include access to all talks and hands-on workshops, food and drink, evening socials, access to the event app with all attendees and networking functionality and all post-event videos.

You can! Talks will be reviewed by committee and selected based on relevance, novelty, and clarity of message. Please see our Call for Speakers page

Talk: Scaling AI: Observability Across Models, Data Pipelines, and Infrastructure

Presenter:
George Miranda, VP of Marketing @ InsightFinder AI

About the Presenter:
Currently VP of Marketing for InsightFinder AI. A former engineer turned GTM strategist and intrapreneur, I work for DevTools companies with deeply technical products and complex value props. Previously held marketing and product leadership roles with Honeycomb.io and PagerDuty.

About the Company:
InsightFinder AI leverages patented unsupervised machine learning algorithms to solve the toughest problems in enterprise AI and IT management. Built on real-time anomaly detection, root cause analysis, and incident prediction, InsightFinder AI delivers AI Observability and IT Observability solutions that help enterprise-scale organizations to automatically identify, diagnose, and remediate issues including model drift, LLM hallucinations, model data quality, and application and infrastructure failures.

Talk Track: Agent Lifecycle Management

Talk Abstract:
As AI models move from pilot to production environments, ensuring AI model reliability and performance becomes increasingly difficult. Traditional monitoring approaches fall short when it comes to identifying the interactions between model behavior, data quality, and infrastructure health. In this talk, I will explore the key challenges in delivering reliable and responsible enterprise AI and introduce a new approach to intelligent and efficient monitoring, evaluation, and governance that is designed to meet these challenges. I will share real-world case studies that highlight the importance of these techniques and how these techniques enhance trust, accountability, and performance in enterprise AI deployments.

Attendees will learn:
* Why conventional observability tools are insufficient for enterprise-scale AI/ML systems
* A practical approach for detecting and mitigating model and data drift, data quality challenges, LLM hallucinations, and malicious prompt injections
* Techniques for correlating infrastructure anomalies with model behavior in production
* Best practices for scaling reliable, cost-efficient AI systems

Talk: Get RAG into Production in 15 Minutes

Presenter:
Rajiv Shah, Chief Evangelist @ Contextual AI

About the Presenter:
Rajiv Shah is the Chief Evangelist at Contextual AI with a passion and expertise in Practical AI. He focuses on enabling enterprise teams to succeed with AI. Rajiv has worked on GTM teams at leading AI companies, including Hugging Face in open-source AI, Snorkel in data-centric AI, Snowflake in cloud computing, and DataRobot in AutoML. He started his career in data science at State Farm and Caterpillar.

Rajiv is a widely recognized speaker on AI, published over 20 research papers, been cited over 1000 times, and received over 20 patents. His recent work in AI covers topics such as sports analytics, deep learning, and interpretability.

Rajiv holds a PhD in Communications and a Juris Doctor from the University of Illinois at Urbana Champaign. While earning his degrees, he received a fellowship in Digital Government from the John F. Kennedy School of Government at Harvard University. He is well known on social media with his short videos, @rajistics, that have received over ten million views.

About the Company:
Contextual AI’s mission is to change the way the world works through AI. Leveraging our RAG 2.0 technology, our team is advancing specialized RAG agents that address the most complex and knowledge-intensive enterprise use cases.

Talk Track: Retrieval-Augmented Generation (RAG)

Talk Abstract:
RAG in 15 minutes? Let me show you how to build an end-to-end Agentic RAG pipeline and demonstrate its integration with MCP. I will cover all the components in a RAG system and what you should be looking for. By the end, you will have an improved understanding of what a good RAG system looks like. I will also show you how to deploy RAG in minutes using Contextual AI’s managed RAG solution.

Talk: Mission: Data Possible – Rethinking Data Architectures for GenAI

Presenter:
Jörg Schad, PhD, Head of Engineering @ Nextdata

About the Presenter:
Dr. Jörg Schad has been working on the intersection of data management, databases, and machine learning. Currently, he is focused on operationalizing decentralized data management systems with the help of Data Mesh. In his previous life, he enjoyed working with graph databases, analytics, and machine learning as CTO at ArangoDB, building data and machine learning infrastructure in healthcare at Suki AI and Mesosphere, and designing in-memory databases with SAP. Jörg obtained a Ph.D. in distributed databases and data analytics and enjoys discussing the latest trends in databases and management.

About the Company:
Nextdata is pioneering the future of data infrastructure with its AI-native platform for autonomous data products. Designed for enterprises building modern AI, analytics, and application systems, Nextdata OS enables data to be self-describing, self-governing, and self-orchestrating—eliminating the need for brittle pipelines and centralized control. Founded by Zhamak Dehghani, creator of the data mesh, Nextdata empowers teams to publish and consume data products as modular, policy-aware services. The result: faster, safer, and more scalable access to high-quality data, ready for machine-scale use by agents, models, and developers alike. Nextdata is redefining how data delivers value.

Talk Track: Data Pipelines and Preprocessing for GenAI

Talk Abstract:
As enterprises move from GenAI prototypes to production systems, a core limitation is becoming clear: it’s not the models—it’s the data infrastructure. Most existing stacks were built for dashboards and reports, not autonomous agents that continuously consume, reason over, and act on data in real time.
The autonomous consumption of data by LLMs poses — or reinforces — several challenges in data management:
* Task-specific data discovery and access, providing relevant context without confusion of unnecessary context
* Safe data access with both high-quality data and without exposing sensitive information
* Autonomous speed and frequency of data access

In this session, Jörg Schad presents a developer-centric framework for building AI-native data infrastructure, designed from the ground up to support GenAI and autonomous workflows. By relying on standardized interfaces of autonomous data products, this approach offers multiple benefits over traditional, pipeline-heavy data pipelines, including significantly faster productionization of GenAI prototypes.

Whether you’re building internal copilots or automating business workflows with agents, this session will show you how to bridge the gap between GenAI models and the data infrastructure they need to thrive.

Talk: NVIDIA Dynamo Platform: Scale and Serve Generative AI, Fast.

Presenter:
Chris Alexiuk, Product Research Engineer @ NVIDIA

About the Presenter:
Chris Alexiuk is a Product Research Engineer and Developer Advocate at NVIDIA, where he drives innovation in generative AI. He specializes in:

– Reinforcement-learning-based reasoning models and test-time scaling
– GPU optimization and CUDA kernel acceleration for large-scale inference
– Retrieval-augmented generation (RAG) architectures and agentic AI integrations

Chris has delivered numerous technical talks, authored industry-leading blogs, and contributes to open-source AI research, empowering developers to build efficient, real-world GenAI solutions.

About the Company:
NVIDIA is the Engine of AI NVIDIA engineers the most advanced chips, systems, and software for the AI factories of the future. We build new AI services that help companies create their own AI factories..

Talk Track: Performance Tuning and Latency Optimization

Talk Abstract:
The NVIDIA Dynamo Platform is a high-performance, low-latency inference platform designed to serve all AI models—across any framework, architecture, or deployment scale. Whether you’re running image recognition on a single entry-level GPU or deploying billion-parameter large language reasoning models across hundreds of thousands of data center GPUs, the NVIDIA Dynamo Platform delivers scalable, efficient AI inference.

Talk: Securing AI Agents Through Continuous Red Teaming

Presenter:
Alex Combessie, Co-founder & Co-CEO @ Giskard.AI

About the Presenter:
Alex is the co-founder and CEO at Giskard, a startup dedicated to secure AI agents through exhaustive testing. Previous experience includes big data & analytics consulting at Capgemini, and lead data scientist at Dataiku where he worked the development of the NLP and time-series stack.

At Giskard, he’s leading a team developing an AI testing platform that advances Responsible AI, enhancing business performance while respecting the rights of citizens.

About the Company:
Founded in 2021, Giskard is a French leader in reliability & security of AI systems. Giskard offers an open-source solution, as well as an enterprise LLM Evaluation Hub to continuously test LLM-based applications. With these tools, companies can avoid the risks of hallucinations and security flaws in LLM agents, ensuring their quality, safety and security. Giskard is used by global companies such as AXA, BNP PF, Michelin, BPCE or SG to secure their AI systems. Giskard is funded by public and private investors, including the European Commission (EIC Accelerator), Bpifrance, Elaia, Bessemer, the CTO of Hugging Face, and more.

Talk Track: Agentic Evaluation Strategies

Talk Abstract:
Learn best practices & methods of Continuous Red Teaming to protect your LLM agents from emerging issues like sycophancy, prompt injections and inappropriate moderation. We’ll present how regulated enterprises can automate LLM security evaluation, detect LLM risks before they become incidents, and ensure continuous protection of LLM agents.