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.

Curious about how Sifflet can transform the way your team works with data?

Join our 30-min biweekly demo to see how data leaders, engineers, and platform teams use Sifflet to detect, resolve, and prevent issues, before they impact the business.

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Sifflet Live Demo

From drawing lineage between repos, rapid refactoring, and daily testing and monitoring at scale, Callum O’Connor from Adaptavist will show you 3 ways that data observability can speed up your operations so you can work smarter and sharper as a data engineer and gain hundreds of hours of productivity back. 


3 Ways Data & Analytics Engineers Can Work Up to 90% Faster With Data Observability 

Get ready for an exclusive, action-packed webinar led by Sifflet's Chief Product Officer, Wissem Fathallah! He’ll take you on a thrilling journey through Sifflet’s game-changing 2024 features, showing how they help you tackle data incidents faster and smarter than ever before. From groundbreaking monitoring consolidation and intuitive wizard tools to innovations like data quality as code, a revamped dbt integration, and the powerhouse that is Sifflet Insights, this is the ultimate 2024 wrap-up you don’t want to miss. But that’s not all—Wissem will also unveil what’s next for 2025, including the cutting-edge Sifflet AI Agent, expanded integrations, reinforced data lineage, and more surprises that will keep Sifflet at the forefront of data observability. Mark your calendar for January 22nd and get an exclusive glimpse into the future of data observability. Trust us, you’ll leave inspired and excited for what’s to come!


Shaping the Future of Data Observability: Sifflet's 2024 Top Features and What's Next

At Sifflet, we don’t see AI as a magic fix – we see it as a way to reach our real goal: making data clarity accessible, reliable, and solvable for everyone in your organization. Our AI features are here to cut through the noise, empowering your technical teams to zero in on what truly matters while making data observability intuitive and accessible company-wide.

In this webinar, we’ll share how Sifflet’s AI-driven tools make a real difference – from setting up monitoring in a few clicks to spotting anomalies before they become problems. Expect more than a simple plug-and-play with ChatGPT; this is about practical, intelligent automation that delivers. Join Eric as he dives into the specific features designed to make your data work easier, faster, and more reliable. See you there!


3 Ways AI-Powered Data Observability Can Make Your D&A Teams Way More Efficient

Join us for an insightful journey into the world of data observability with Sami Rahman, the Director of Data at Hypebeast. Discover how data quality and observability can transform your business operations and enhance collaboration between technical and non-technical teams. Sammy shares real-world experiences and practical strategies that have helped Hypebeast streamline processes and improve data trust with Sifflet.

Whether you're just starting with data observability or looking to refine your approach, this webinar offers valuable insights and actionable advice.

Don't miss the chance to learn from industry experts and elevate your data game!


Hypebeast Success Story: when Hype meets Data Observability

Join us as we dive into the intriguing world of data observability and the classic build versus buy debate.

Uncover the secrets behind successful in-house solutions and when it's time to consider third-party software with the CTO from Carrefour. Learn about the pivotal moments that signal a need for change and how to navigate them. Explore the benefits of scaling up with external vendors and the impact on business teams.

Don't miss out on the opportunity to enhance your data strategy. Watch now to unlock the full potential of your data initiatives!


Navigating the Build vs. Buy Dilemma in Data Observability

As 2025 approaches, data observability is rapidly gaining momentum in the market, with most companies recognizing the critical role of reliable data in the success of AI and data projects. However, this realization brings a host of questions: How do you begin implementing holistic data observability? When is the right time to start? What tech stack is necessary to make it work? How can you ensure your teams adopt it effectively? And how do you measure and demonstrate its impact? Salma Bakouk will highlight key trends that can guide you in scaling data observability successfully.


Get Data Observability ready for 2025: 5 key considerations for CDOs

As data leaders, you know the struggle of dealing with fragmented tools, endless incident backlogs, and the pressure to ensure data quality across your organization. In this 45m webinar, we’ll explore how a holistic approach to data observability can alleviate these challenges.

Through real-world examples, we’ll show how Sifflet helps unify data accessibility, reliability, and traceability into one seamless experience. Say goodbye to reactive firefighting and hello to proactive data quality management that empowers your entire organization. Learn how to reduce resolution time, foster cross-team collaboration, and build a culture of trust in your data.

This session is designed to address the core challenges you face every day and give you the tools to build a more efficient, trustworthy, and scalable data infrastructure.


Mastering Holistic Data Observability: A Blueprint for Data Leaders

AI initiatives collapse not because of models, but because of the data beneath them. In this opening conversation, Sanjeev and Salma frame the executive challenge: how enterprises can design for reliability from ingestion to insight. Expect sharp takes on why trust is becoming the new KPI for AI success.


Opening Keynote: Modern Reliability in the Age of AI

dbt transformed how teams build with data; observability defines how teams trust what they build. In this fireside, Tristan and Salma explore how a trust layer is emerging alongside transformation and semantic layers — and why reliability, quality, and transparency are now essential guardrails for modern analytics.


Fireside Chat: The Trust Layer: From Transformation to Observability

Metadata is more than documentation, it’s the connective tissue for observability, lineage, and scale. Tomas explains how metadata-centric architectures create durable trust in modern data platforms.


Metadata as Architecture: Why the Future of Data Trust Starts Here

Contracts and lineage are hot topics, but what really scales in practice? Practitioners share candid lessons on designing observability that works in production environments.


Data Contracts, Metadata, and Lineage: What Actually Works?

The modern data stack promised speed and flexibility, but reliability still lags behind. In this keynote, Joe Reis argues that observability isn’t a feature you add later, it’s an architectural principle you must design from day one. A pragmatic call to rethink reliability as the core of your data platform.


Beyond the Modern Data Stack: Why Architecture Is the Real Source of Trust

At Shopify, Solmaz built data products where adoption hinged on trust. In this conversation with Salma, she shares lessons on designing for reliability, explainability, and user confidence when business outcomes depend on it. From fraud detection to merchant payouts, this fireside shows why in data products, trust isn’t a feature, it’s the product.


Fireside: Designing Data Products People Trust

Most governance frameworks crumble under scale. Mahdi reveals how metadata-driven observability is making compliance and control possible without slowing teams down. Expect real-world insights into lineage, policy enforcement, and embedding trust into the data fabric.


Governance That Scales: How Metadata Powers Compliance and Control

From global supply chains to customer-facing data products, Maxime and Alejandro share how enterprises are scaling observability and why changing processes is harder than changing tools.


Enterprise Case Study: Data Observability in Complex Enterprises

Governance used to mean gatekeeping. Today it must balance agility with accountability. In this panel, senior leaders debate how observability reshapes governance strategies, how to operationalize lineage for risk management, and how enterprises can design governance that unlocks innovation instead of stifling it.


The New Trust Equation: Observability Meets Governance

AI is everywhere, but dependable AI is rare. In this keynote, Ben Castleton cuts through the agentic hype to show what it really takes to deploy AI systems that work in practice. Expect candid insights on pipelines, monitoring, and why “self-healing” is harder than most vendors admit.


AI Without Illusions: Separating Hype from Deployable Reality

Self-service and AI queries open new opportunities, but also risks of inconsistency and mistrust. Colin explores how governance and semantic models ensure trust doesn’t collapse as access expands.


Building Trust at the Edge of AI: Ensuring Governance When Every User Can Ask a Question

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

From Airflow to MCPs, Maxime outlines how infrastructure is evolving to support adaptive, trustworthy workflows at scale.


The Promise of MCP-Powered Workflows: A New Operating System for Data

As enterprises rush into AI, scalable infrastructure must also be secure and trustworthy. Seth shares Snowflake’s perspective on aligning infrastructure, observability, and governance to support reliable AI adoption.


Trust at Scale: Building AI-Ready Platforms in the Cloud Era

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.
