Sifflet is the leading data observability platform that delivers data trust at scale for analytics and AI initiatives by bridging the gap between technical and business users.  Global customers like the Penguin Random House, Carrefour, Auchan, CMA CGM and Adaptavist rely on Sifflet to reach and maintain high levels of data quality and reliability needed for business critical analytics and AI.  Sifflet is a best-in-class data observability solution for the entire organization, ranked Best estimated ROI and Fastest implementation by G2 users. 

Sifflet, the AI-augmented data observability platform built for data teams with business users in mind.

The summit closes with a manifesto-style discussion on what “trust by design” really means for the next decade of data and AI. Our panelists reflect on the week’s conversations, share their visions for the future, and lay out the principles that will define trustworthy data systems at enterprise scale.


Trust by Design: A Manifesto for Data in the AI Era

As AI adoption accelerates, organizations face a new and complex attack surface. This talk breaks down the essential governance, security, and data-quality controls needed to build safe, compliant, and trustworthy AI, illustrated through Snowflake’s defense-in-depth approach.


Best Practices for AI Governance and Security 

What happens when AI becomes an active participant in the data engineering loop? In this session, Maxime Beauchemin gives a first look at AGOR, his new agentic coding environment, and demonstrates how tools like Claude Code and Codex can generate pipelines, reason about metadata, and accelerate engineering work in real time.


The AGOR Experiment: A First Look at Agentic Coding for Data Teams

Airbyte CEO Michel Tricot explores how enterprises can accelerate AI adoption without sacrificing data control. Learn how sovereign data movement architectures enable AI agents to access comprehensive data across systems while maintaining security boundaries, preserving metadata, and meeting compliance requirements, unlocking AI deployment at scale


Increasing AI Adoption through Sovereign Data Movement

As data platforms grow, they often become black boxes. How do you ensure reliability and trust without slowing down innovation? Mahdi reveals how to build a scalable data observability practice fueled by active metadata. Discover real-world strategies for using metadata to power governance at scale, implement policy-based monitoring, and leverage AI to detect anomalies before they impact users. This session provides a blueprint for embedding trust and control directly into your data fabric, enabling teams to move faster, with confidence.


The Observability Engine: Scaling Data Trust with Active Metadata

Speaker

Mahdi Karabiben

Head of Product & Data @Sifflet

Replays

Trust by Design: A Manifesto for Data in the AI Era

Best Practices for AI Governance and Security