Agorify

8:00 AM

8:30 AM

Registration Opens

8:30 AM

8:40 AM

Welcoming Notes and Orientation

8:40 AM

9:00 AM

Chairman’s Opening Remarks

9:00 AM

9:20 AM

Future Outlook Session

9:20 AM

9:40 AM

KEYNOTE | The Age of Applied Intelligence: Turning Data & AI Into Enterprise Capability

9:45 AM

10:05 AM

KEYNOTE | The Economics of AI and the Changing Cost, Value and Consumption of Enterprise Intelligence

10:05 AM

10:25 AM

Networking Coffee & Peer-to-Peer Meetings

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M10] - Industrial AI & Physical AI Spotlight

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M1] - Machine Learning, Agents & Generative AI Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M2] - Data Engineering & Data Ops Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M3] - Data Platform & Architecture Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M4] - Data Strategy & Governance Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M5] - Analytics & Decision Intelligence Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M6] - AI Strategy & Governance Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M7] - AI Infrastructure & Operations Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M8] - AI Automation & Transformation Stage

10:30 AM

10:40 AM

Moderator’s Opening Remarks

[M9] - Databases, Context & Data Quality Stage

10:40 AM

11:00 AM

How Do You Move Industrial AI From Successful Pilots to Production Across Multiple Factories and Sites?

[M10] - Industrial AI & Physical AI Spotlight

10:40 AM

11:00 AM

How Do You Make Agents Accurate Instead of Confident by Engineering an Enterprise Context Layer?

[M1] - Machine Learning, Agents & Generative AI Stage

10:40 AM

11:00 AM

How Do You Ship Data Faster Without Losing Trust by Engineering Quality, Testing and Observability Into Every Pipeline?

[M2] - Data Engineering & Data Ops Stage

10:40 AM

11:00 AM

How Do You Re-Architect Your Data Platform for AI Without Rebuilding Everything You Already Have?

[M3] - Data Platform & Architecture Stage

10:40 AM

11:00 AM

How Do You Redesign Your Data Strategy When AI Becomes One of the Biggest Consumers of Enterprise Data?

[M4] - Data Strategy & Governance Stage

10:40 AM

11:00 AM

How Do You Move From Measuring Business Performance to Actually Improving It by Building Analytics Around Decisions?

[M5] - Analytics & Decision Intelligence Stage

10:40 AM

11:00 AM

How Do You Turn an AI Strategy Into an Enterprise Operating Model That Can Actually Deliver at Scale?

[M6] - AI Strategy & Governance Stage

10:40 AM

11:00 AM

Where Should Enterprise AI Actually Run - Public Cloud, Private Cloud, On-Prem or Hybrid?

[M7] - AI Infrastructure & Operations Stage

10:40 AM

11:00 AM

How Do YouDecide Whatto Automate, Whatto Augment and What Should StayHuman?

[M8] - AI Automation & Transformation Stage

10:40 AM

11:00 AM

How Do You Fix theDataQuality Problems That Keep AI and Agents From Reaching Production?

[M9] - Databases, Context & Data Quality Stage

11:10 AM

11:30 AM

How Do You Build an Industrial Data Foundation When Critical Data Is Spread Across Machines, Sensors, Historians, MES, ERP and the Cloud?

[M10] - Industrial AI & Physical AI Spotlight

11:10 AM

11:30 AM

How Do You Prove Your LLM Applications and Agents Actually Work by Building Offline and Online Evaluation Pipelines?

[M1] - Machine Learning, Agents & Generative AI Stage

11:10 AM

11:30 AM

How Do You Feed AI Agents With Fresh Data by Turning Streaming Into the Real-Time Nervous System of the Enterprise?

[M2] - Data Engineering & Data Ops Stage

11:10 AM

11:30 AM

Is the Semantic Layer Becoming the Most Important Infrastructure Layer for Enterprise AI?

[M3] - Data Platform & Architecture Stage

11:10 AM

11:30 AM

What Separates Organisations That Scale AI From Those That Don’t by Treating AI-Ready Data as an Operating Model Rather Than Another Data Project?

[M4] - Data Strategy & Governance Stage

11:10 AM

11:30 AM

What Happens to BI When Dashboards Are No Longer the Only Way People Consume Analytics?

[M5] - Analytics & Decision Intelligence Stage

11:10 AM

11:30 AM

Which AI Projects Should You Kill? Escaping the Pilot Graveyard by Governing the Portfolio Around Value

[M6] - AI Strategy & Governance Stage

11:10 AM

11:30 AM

How Do You Build Infrastructure That Can Scale From AI Experiments to Thousands of Production Workloads?

[M7] - AI Infrastructure & Operations Stage

11:10 AM

11:30 AM

How Do You Redesign End-to-End Workflows Around AI Instead of Automating the Way WorkHas Always BeenDone?

[M8] - AI Automation & Transformation Stage

11:10 AM

11:30 AM

What Changes in Your Database Architecture When AI Agents Become Major Consumers and Creators of Enterprise Data?

[M9] - Databases, Context & Data Quality Stage

11:40 AM

12:00 PM

What Is Physical AI and How Is It Changing Robotics, Automation and Industrial Operations?

[M10] - Industrial AI & Physical AI Spotlight

11:40 AM

12:00 PM

What Happens When Agents Start Building and Repairing Data Pipelines Instead of Just Consuming Them?

[M2] - Data Engineering & Data Ops Stage

11:40 AM

12:00 PM

How Do You Build an Enterprise Context Layer That Gives Humans and AI Agents the Same Understanding of Your Business?

[M3] - Data Platform & Architecture Stage

11:40 AM

12:00 PM

How Do You Make Governance Enforceable by Turning Policy Documents Into Automated, Machine-Verifiable Controls?

[M4] - Data Strategy & Governance Stage

11:40 AM

12:00 PM

How Do You Build a KPI and Metrics Framework That Gives the Entire EnterpriseOne Trusted Version of Performance?

[M5] - Analytics & Decision Intelligence Stage

11:40 AM

12:00 PM

How Do You Prove AI ROI Before the CFO Starts Deferring the Next Round of Investment?

[M6] - AI Strategy & Governance Stage

11:40 AM

12:00 PM

How Do You Control the Infrastructure and Inference Cost of Enterprise AI Before Usage Explodes?

[M7] - AI Infrastructure & Operations Stage

11:40 AM

12:00 PM

How Do You Move FromAI-AssistedTasks to End-to-EndIntelligent AutomationWithout AutomatingBrokenProcesses?

[M8] - AI Automation & Transformation Stage

11:40 AM

12:00 PM

Do AI Agents Need Their Own Memory Store and What Should Actually Be Remembered, Retrieved or Forgotten?

[M9] - Databases, Context & Data Quality Stage

12:10 PM

12:30 PM

How Do You Use AI to Optimize Production in Real Time Without Disrupting the Processes Already Running the Factory?

[M10] - Industrial AI & Physical AI Spotlight

12:10 PM

12:30 PM

How Do You Expose Enterprise Tools andData to Agents Safely and at Scale by Putting MCP Into Production?

[M1] - Machine Learning, Agents & Generative AI Stage

12:10 PM

12:30 PM

How Do You Make Documents, Images, Audio and Other Unstructured Data Production-Ready for Enterprise AI?

[M2] - Data Engineering & Data Ops Stage

12:10 PM

12:30 PM

What Should Your Data Platform Look Like When AI Agents Become First-Class Consumers and Actors Across Enterprise Data?

[M3] - Data Platform & Architecture Stage

12:10 PM

12:30 PM

How Do You Control What Agents Can See and Do by Designing Data Access, Purpose Limitation and Audit for Autonomous Systems?

[M4] - Data Strategy & Governance Stage

12:10 PM

12:30 PM

How Do You Make Self-Service Analytics Actually Self-Service Without Creating Thousands of Conflicting Answers?

[M5] - Analytics & Decision Intelligence Stage

12:10 PM

12:30 PM

When Should You Use a Frontier Model, Smaller Model or Multiple Models by Routing Every Workload to the Right Cost and Performance Tier?

[M6] - AI Strategy & Governance Stage

12:10 PM

12:30 PM

What Changes in Your Infrastructure When AI Agents Run Continuously Instead of Waiting for Human Prompts?

[M7] - AI Infrastructure & Operations Stage

12:10 PM

12:30 PM

How Do YouUse Process Intelligence to Identify What Should Be Automated, Redesigned or Eliminated?

[M8] - AI Automation & Transformation Stage

12:10 PM

12:30 PM

Vector,Graph orHybrid Search:How Do You Choose the Right Retrieval Architecture for Enterprise AI?

[M9] - Databases, Context & Data Quality Stage

12:35 PM

12:55 PM

KEYNOTE | The Agentic Enterprise and How AI That Can Reason, Decide and Act Is Changing the Way We Build and Run Business

12:50 PM

1:40 PM

Networking Lunch

1:40 PM

2:00 PM

How Do You Deploy Industrial AI at the Edge When Latency, Connectivity, Cost or Sovereignty Make Cloud-Only AI Impractical?

[M10] - Industrial AI & Physical AI Spotlight

1:40 PM

2:00 PM

How Do You Deliver End-to-End Business Workflows by Orchestrating Specialised Agents?

[M1] - Machine Learning, Agents & Generative AI Stage

1:40 PM

2:00 PM

How Do You Stop Upstream Changes Breaking Everything Downstream by Making Data Contracts Work at Enterprise Scale?

[M2] - Data Engineering & Data Ops Stage

1:40 PM

2:00 PM

How Do You Design Hybrid and Sovereign Data Platforms Without Sacrificing Scalability, Performance or Access to AI?

[M3] - Data Platform & Architecture Stage

1:40 PM

2:00 PM

Can AI Agents Govern Data Too by Automating Classification, Lineage, Quality and Stewardship

[M4] - Data Strategy & Governance Stage

1:40 PM

2:00 PM

When Do Predictive Models Still Create More Business Value Than Generative AI?

[M5] - Analytics & Decision Intelligence Stage

1:40 PM

2:00 PM

Should AI Be Centralized, Federated or Embedded and What Operating Model Works Once Every Business Function Is Building With AI?

[M6] - AI Strategy & Governance Stage

1:40 PM

2:00 PM

How Do You Build an Enterprise AI Factor That Turns Shared Compute, Data and Platforms Into Production AI at Scale?

[M7] - AI Infrastructure & Operations Stage

1:40 PM

2:00 PM

What Comes Afterthe Copilot by Moving From AI Assistance to Agents That Execute Work?

[M8] - AI Automation & Transformation Stage

1:40 PM

2:00 PM

How Do YouGive AI Reliable Context by Combining Semantic Search, Structured Data and Enterprise Knowledge?

[M9] - Databases, Context & Data Quality Stage

2:10 PM

2:30 PM

How Do You Run Physical AI in Real Time by Bringing Perception, Reasoning and Decision-Making to the Edge?

[M10] - Industrial AI & Physical AI Spotlight

2:10 PM

2:30 PM

When Do You Beat Frontier Models on Cost, Latency and Accuracy by Fine-Tuning Small,Domain-Specific Models Instead of Prompting?

[M1] - Machine Learning, Agents & Generative AI Stage

2:10 PM

2:30 PM

Can Data Quality Gates in CI/CD Stop Bad Data Before It Ever Reaches Production?

[M2] - Data Engineering & Data Ops Stage

2:10 PM

2:30 PM

Which Data Architecture Will Still Matter in Five Years and Which Decisions Are You About to Regret?

[M3] - Data Platform & Architecture Stage

2:10 PM

2:30 PM

Who Owns the Data? Turning Accountability From a Governance Diagram Into Something That Actually Works Across the Enterprise

[M4] - Data Strategy & Governance Stage

2:10 PM

2:30 PM

How Do You Forecast Demand, Revenue and Risk When Historical Patterns Keep Breaking?

[M5] - Analytics & Decision Intelligence Stage

2:10 PM

2:30 PM

How Much Autonomy Should You Give an AI Agent by Matching Governance to the Risk of What It Can Actually Do?

[M6] - AI Strategy & Governance Stage

2:10 PM

2:30 PM

How Do You Get More From Expensive GPUs by Increasing Utilization Across Training, Fine-Tuning and Inference Workloads?

[M7] - AI Infrastructure & Operations Stage

2:10 PM

2:30 PM

How Do You Build Agentic Workflows That Coordinate Across Applications, Data and Business Processes?

[M8] - AI Automation & Transformation Stage

2:10 PM

2:30 PM

Is Postgres Becoming the Default Database for AI Applications—or Are We Asking It to Do Too Much?

[M9] - Databases, Context & Data Quality Stage

2:40 PM

3:00 PM

How Do You Turn Industrial Data Into Real-Time Decisions by Combining AI With Sensor, Machine and Operational Data?

[M10] - Industrial AI & Physical AI Spotlight

2:40 PM

3:00 PM

How Do You Scale Agentic Coding Without Slowing Engineering Down by Governing AI Coding Agents Properly?

[M1] - Machine Learning, Agents & Generative AI Stage

2:40 PM

3:00 PM

How Do You Stop Data Engineers From Firefighting by Detecting Pipeline Failures Before Users and Agents Find Them?

[M2] - Data Engineering & Data Ops Stage

2:40 PM

3:00 PM

Can Transactional and Analytical Systems Finally Converge to Give AI Real-Time Access Without Endless Data Copies?

[M3] - Data Platform & Architecture Stage

2:40 PM

3:00 PM

How Do You Make Federated Governance Work by Giving Domains Autonomy Without Losing Enterprise Consistency?

[M4] - Data Strategy & Governance Stage

2:40 PM

3:00 PM

How Do You Know What Actually Caused a Business Outcome Instead of Mistaking Correlation for Causation?

[M5] - Analytics & Decision Intelligence Stage

2:40 PM

3:00 PM

What Comes After Human-in-the-Loop When Thousands of Agent Decisions Make Manual Approval Impossible?

[M6] - AI Strategy & Governance Stage

2:40 PM

3:00 PM

When Should You Buy AI Compute, Rent It in the Cloud or Consume It as a Service?

[M7] - AI Infrastructure & Operations Stage

2:40 PM

3:00 PM

How Do You Orchestrate Humans, AI Agents and Traditional Automation Across One End-to-End Process?

[M8] - AI Automation & Transformation Stage

2:40 PM

3:00 PM

How Do You Make Unstructured Enterprise Data Ready for Retrieval, Reasoning and Agentic AI?

[M9] - Databases, Context & Data Quality Stage

3:10 PM

3:40 PM

Networking Coffee & Peer-to-Peer Meetings

3:40 PM

4:05 PM

Technology in practice | Round 1

4:10 PM

4:30 PM

What Happens When AI Agents Move Beyond Software and Start Interacting With Machines, Robots and Industrial Control Systems?

[M10] - Industrial AI & Physical AI Spotlight

4:10 PM

4:30 PM

How Do You Stop Wrong Answers Reaching Stakeholders by Verifying andGrounding AI-Generated Responses?

[M1] - Machine Learning, Agents & Generative AI Stage

4:10 PM

4:30 PM

When Does Real-Time Data Actually Create Business Value—and When Is Batch Still the Better Engineering Decision?

[M2] - Data Engineering & Data Ops Stage

4:10 PM

4:30 PM

How Do You Connect Data Across Clouds, SaaS and Legacy Systems by Federating Metadata and Catalogs Instead of Moving Everything?

[M3] - Data Platform & Architecture Stage

4:10 PM

4:30 PM

How Do You Deliver Data in a Federated Organisation by Treating Data Products as an Ownership, Funding and Lifecycle Model?

[M4] - Data Strategy & Governance Stage

4:10 PM

4:30 PM

How Do You Turn Predictions Into Better Actions by Combining Analytics With Optimization and Operations Research?

[M5] - Analytics & Decision Intelligence Stage

4:10 PM

4:30 PM

How Do You Know Which AI Systems You Actually Have by Building a Live Inventory of Models, Agents, Tools and Dependencies?

[M6] - AI Strategy & Governance Stage

4:10 PM

4:30 PM

How Do You Build an Inference Infrastructure Strategy When Serving Models Becomes a Bigger Workload Than Training Them?

[M7] - AI Infrastructure & Operations Stage

4:10 PM

4:30 PM

How Much Autonomy Should You Give an AI Agent Before Automation Becomes an Operational Risk?

[M8] - AI Automation & Transformation Stage

4:10 PM

4:30 PM

Why IsData Modelling Back—and What Changes When Both Humans and AI Need to Understand the Model?

[M9] - Databases, Context & Data Quality Stage

4:40 PM

5:00 PM

From Predictive to Prescriptive Maintenance: How Do You Move From Predicting Failure to Deciding What Action to Take?

[M10] - Industrial AI & Physical AI Spotlight

4:40 PM

5:00 PM

How Do You Stop Wrong Answers Reaching Stakeholders by Verifying and Grounding AI-Generated Responses?

[M1] - Machine Learning, Agents & Generative AI Stage

4:40 PM

5:00 PM

How Do You Scale From a Few Data Products to Hundreds Without Creating an Ownership, Dependency and Orchestration Nightmare?

[M2] - Data Engineering & Data Ops Stage

4:40 PM

5:00 PM

How Do You Escape Platform Lock-In Without Giving Up the Productivity of an Integrated Data and AI Stack?

[M3] - Data Platform & Architecture Stage

4:40 PM

5:00 PM

When Is a Data Product Actually a Product and How Do You Measure Whether Anyone Uses It or Values It?

[M4] - Data Strategy & Governance Stage

4:40 PM

5:00 PM

When Does Real-Time Analytics Improve a Decision Enough to Justify the Cost and Complexity?

[M5] - Analytics & Decision Intelligence Stage

4:40 PM

5:00 PM

How Do You Govern AI You Didn’t Build by Managing Risk Across Foundation Models, Vendors and Third-Party Agents?

[M6] - AI Strategy & Governance Stage

4:40 PM

5:00 PM

How Do You Scale Storage for AI When Structured Data, Documents, Images, Video and Model Data All Compete forPerformance?

[M7] - AI Infrastructure & Operations Stage

4:40 PM

5:00 PM

What Happens to RPA and Traditional Automation When AI Agents Can Reason, Decide and Act?

[M8] - AI Automation & Transformation Stage

4:40 PM

5:00 PM

How Do You Reinvent Master Data Management When AI Agents Need a Trusted View of Customers, Products and Suppliers?

[M9] - Databases, Context & Data Quality Stage

5:10 PM

5:30 PM

KEYNOTE | The AI-Enabled Enterprise and the Redesign of Work, Processes and Operating Models Around Human and Machine Intelligence

5:35 PM

5:55 PM

Chairman’s Closing Remarks in the Plenum Area

5:45 PM

6:30 PM

6:30 PM

8:30 PM

Data and AI Readiness (DAIR) Awards