Conf42 MLOps 2025 - Online

September 18 2025 - premiere 5PM GMT

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TRACKS:

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MLOps in Healthcare: Scaling AI Model Deployment Through Strategic Automation and Monitoring Frameworks

Aishwarya Pai

Deloitte

From Cloud to Edge: How On-Device AI Delivers 90%+ Performance Gains While Slashing Costs

Anushree Nagvekar

AEye Inc

Monitoring Production Grade Agentic Rag Pipelines

Jayita Bhattacharyya

Deloitte

Human-in-the-Loop MLOps: Production Patterns That Boost Model Performance 40% While Maintaining Human Control

Tejasvi Nuthalapati

Amazon

Production-Ready NLP Systems: From Sales Quote Generation to 87% Performance Gains Through MLOps Best Practices

Vani Pangulur

Snowflake

Scaling Educational AI at the Edge: MLOps Strategies for Low-Code Platforms in Resource-Constrained Environments

Lalitha Potharalanka

FDA

Intelligent Error Response: How ML-Driven Slack Integration Cut MTTR by 88.5% Across 17 Enterprise Systems

Sreelatha Pasuparthi

Liberty Mutual Insurance

MLOps in Action: Transforming Insurance Identity Verification with Cloud, AI, and Blockchain

Shikha Gurjar

Guidewire Software

Cloud-Powered MLOps for Scalable, Smart, and Resilient EV Charging Systems

Preeti Sali

Ford Motor Company

Generative AI in Fintech: From Transactional Data to Personalized Financial Experiences

Pushpalika Chatterjee

The Huntington National Bank

Fail Fast, Recover Faster: Harnessing Cascading Timeouts for Scalable System Resilience

Madhavi Bhairavabhatla

Mastercard

Production-Ready ML: How Data Quality Frameworks Cut Development Cycles by 41%

Ravali Kandur

Roblox

MLOps at Scale: Designing Governed AI Pipelines for Healthcare Impact

Nikitha Edulakanti

Fresenius Medical Care

Scaling AI in Finance: MLOps Strategies Behind $78.6 Billion Market Transformation

Parul Purwar

IMC Trading

Transforming Manufacturing Through AI-Driven Predictive Maintenance: From Reactive Crisis to Proactive Excellence

Muruga Angamuthu

Techtronic Industries - TTI

MLOps at Scale: Operationalizing AI-Driven Network Intelligence in Production Telecom Environment

Ajay Averineni

IBM

MLOps for Critical Infrastructure Security: Deploying, Monitoring, and Scaling AI Defense Models in Production

Anbarasu Aladiyan

Compunnel

MLOps at Trillion-Parameter Scale: Operationalizing Large Language Model Training Pipelines

Anjan Dash

Meta

AI-Driven Cybersecurity: Intelligent Threat Detection and Privacy in the Post-Quantum Era

Arfi Siddik Mollashaik

securiti.ai

AI-Driven Observability: Revolutionizing MLOps Performance Through Proactive Monitoring and Predictive Operations

Bhanu Kolli

Point

Automating AI Ethics: MLOps-Native Data Governance for Production-Ready Generative AI Pipelines

Bhanu Maryala

Informatica

Bridging the MLOps Gap: From AI Research to Production-Ready Systems

Bharath Reddy Baddam

Senior Salesforce Developer New York Life Insurance Company

Network Infrastructure as the Hidden MLOps Bottleneck: Optimizing Data Flow for Modern AI Pipelines

Bhaskararao Vakamullu

Hewlett Packard Enterprise

Embracing Sky Computing: Charting a New Course in AI Cloud Infrastructure

Brian Irish

Ditto

Scaling AI: Fault-Tolerant GenAI Solutions for Millions

Dennis Nerush

Elementor

5-Technology Trends and Opportunities for Start-ups & Fortune 500 Companies

Derris Boomer

BoomerTechnologyGroup.com

MLOps at Scale: Operationalizing Machine Learning for Financial Risk and Fraud Detection in Cloud-Native Environments

Dileep Kumar Kanimetta

Microsoft

The Art of ML Testing: Crafting Tests for Complex AI Systems

Eyal Trabelsi

Bigabid

Building Production-Ready AI Systems: How MCP Servers Enable Scalable MLOps for Enterprise LLM Deployments

Giridhar Raj Singh Chowhan

Microsoft

Operationalizing Enterprise ML at Scale: MLOps Architecture for Legacy-Modern Hybrid Environments

Govinda Komarina

Yash Technologies Inc

From Model to Production: Building Scalable MLOps Pipelines for Enterprise Systems

Jimmy Katiyar

SiriusXM

Operationalizing AI in Finance: MLOps for Scalable BI and Real-Time Analytics

Mallikarjun Ramasani

Barclays

Scaling Conversational AI in Production: MLOps Strategies for Contact Center Transformation and Operational Excellence

Manoj Kumar Vunnava

Godaddy

MLOps at Scale: Real-Time Machine Learning Infrastructure for Smart City Operations

Mayur Bhandari

Microsoft

Building Autonomous MLOps: Self-Healing Infrastructure and AI-Driven Code Evolution

Mohan Singh

Amazon

From Paperwork to Pipeline: Building MLOps for Autonomous Mortgage AI

Naganarendar Chitturi

Newrez

MLOps in FinTech: Architecting Responsible AI at Scale in Regulated Environments

Narasimha Rao Vanaparthi

State Street

Agentic MLOps: Transforming Machine Learning Operations from Manual Monitoring to Autonomous Model Lifecycle Management

Narendra Kumar Reddy Choppa

The Mosaic Company

Production MLOps in Finance: Scaling AI Systems for High-Volume Transaction Processing

Naresh Karri

Intuit

MLOps at Scale

Naveen Edapurath Vijayan

AWS

Deploying AI Literature Agents at Scale: MLOps Strategies for Biomedical Research Platforms

Nishanth Joseph Paulraj

Thermo Fisher Scientific

Production-Ready MLOps for Telecommunications: Neural Network-Based VoIP Monitoring with 88% Accuracy and Automated Deployment Pipelines

Krishna Munnaluru

Oracle

RAG Without the Hassle: Building Scalable AI Apps with OceanBase Vector Database

Peng Wang

OceanBase

Production MLOps for Spam Detection: Real-Time Multi-Modal AI at Billion-User Scale

Prabhakar Singh

Meta

MLOps-Driven Micro-Frontend Architecture: Scaling AI Model Deployment with 47% Faster CI/CD Pipelines and 60% Reduced Model Serving Latency

Praveen Kumar Guguloth

State University of New York

Building MLOps-Ready Data Platforms: Navigating the Evolution from Hadoop to Lakehouse Architectures

Rahul Joshi

Capital One

Scaling MLOps with Self-Service Platforms: Architectures for Automation, Governance, and Velocity

Rajeev Chevuri

Freddie Mac

MLOps at Scale: Production-Ready AI Systems for HR Transformation in Enterprise Shared Service Centers

Ramprasad Reddy Mittana

NSF

MLOps at Scale: Building and Deploying AI Healthcare Systems for Senior Travel Safety

Raphael Shobi Thomas

AI-Driven Insurance Operations: MLOps Strategies Delivering 65% Efficiency Gains and 99% Processing Time Reduction

Sameer Joshi

Cognizant

From PoC to Production: Shipping Enterprise AI Agents with Amazon Bedrock AgentCore

Samuel Baruffi

AWS

When AI Automation Goes Wrong: Real-World MLOps Lessons from Warehouse Deployment Disasters

Shubham Beldar

Symbotic LLC

Breaking the Monolith: How Multi-Agent MLOps Architectures Deliver 40% Faster Model Deployment with Enterprise-Grade Reliability

Sidhanta Panigrahy

Okta

Zero Trust MLOps: Securing AI Pipelines from Development to Production

Sudheer Obbu

JPMorgan Chase

TrendVision: An End-to-End Guide to AI-Powered Marketing Video Generation SaaS Deployment

Taeyang Kim

Pattern

From Code to Configuration: Building Self-Healing Data Pipelines with Metadata-Driven MLOps

Terance Joe Heston Joseph Paulraj

SQA CONCEPTS

Enterprise MLOps Transformation: Scaling Machine Learning Operations Through Microsoft's Integrated Low-Code AI Platform

Venkata Mogili

Northwestern Medicine

Operationalizing AI in Aviation: MLOps Strategies for Predictive Maintenance and Flight Operations at Scale

Vikram Karnam

Delta Air Lines

From YAML to Prompts: How GenAI is Reshaping the Future of MLOps

Vivek Kolasani

NVIDIA

The 18-Minute Revolution: How Zero Trust Transforms MLOps from Security Theater to Operational Reality

Mounika Lakka

UnitedHealth Group, USA.

MLOps Meets Finance: Architecting API-Driven, Intelligent, and Scalable Financial Systems

Anil Kumar Veldurthi

US Bank

Low-Code Meets Public Code: Automating with Minimal Engineering

Anoosha Cherukuri

State of Tennessee

Transparent AI: Building Observable Machine Learning Systems for Financial Compliance

Aparna Thakur

AI-Powered Insurance Recommender Systems: MLOps Automation, Scalable Deployment Pipelines, and Data-Driven Monitoring

Ashish Mohan

University of Connecticut, USA

MLOps for Mission-Critical AI: Threat Detection Pipeline Deployment

Sheela Kakanur Shivayogi

Bapuji Institute of Engineering and Technology

From Lab to Production: Building Scalable MLOps Pipelines That Actually Work - A Data-Driven Blueprint for ML Success

Srikanth Vissarapu

Meta US

MLOps at Scale: Engineering Production ML Systems for Alternative Investment Platforms

Venkata Siva Prasad Bharathula

Google

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