A first look at Sifflet, the data observability platform for data producers and users

In this simple demo, you'll find out how to easily spot an incident, solve it and save your business sanity!

Show Your Stack Who’s Boss

Unified data observability that packs a three-in-one punch. From data discovery to integrated monitoring and troubleshooting capabilities, you’ll be the one in charge.

Seamlessly connect with all your favorite data tools to centralize insights and unlock the full potential of your data ecosystem.
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Join the ranks of happy customers who’ve made Sifflet a G2 leader, trusted for its innovation and impact
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Stay ahead of issues with real-time alerts that keep you informed and in control of your data health
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Organize, discover, and leverage your data assets effortlessly with a smart, searchable catalog built for modern teams.
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Harness the power of AI-driven suggestions to improve efficiency, accuracy, and decision-making across your workflows.
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Empower your team with tailored access, enabling secure collaboration that drives smarter decisions.
What Our Customers Say

See Sifflet in action!

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.

Register for our biweekly demo now!
ACHIEVE

See Data Breakthroughs

Sifflet helps you remove the obstacles that stand in the way of superior insights, value, and products from data. 

Supercharge Productivity 

Data engineers spend up 50% of their time on mundane reliability tasks and data analysts between 40 to 80% of their time vetting data quality. Sifflet augments your team’s capabilities and supercharges their productivity. 

Uplevel Data Reliability
and Quality 

See next-level improvements to data reliability and quality thanks to tools that make it easier and faster than ever to find and fix your data. 

Empower Ownership, Enable Self-Serve 

Sifflet ensures that your colleagues always know the health status of data, can give input to monitors, and take ownership of their data assets. Collaboration with data teams improves and it’s easier to enable data-mesh and self-serve.

TEAMS

Built for

Built for Everyone

Everyone

Data Leaders

Data Engineers

Data Users

Everyone

Sifflet allows everyone to own and build confidence in data thanks to features that make it easy to access, understand and contribute to data reliability and quality.

Data Leaders

Drive innovation and enable AI. With Sifflet, you can transform your data strategy, governance, and team productivity while ensuring efficient and scalable data infrastructure.

Data Engineers

Boost your productivity. Sifflet gives you end-to-end visibility into your architecture, assets, and pipelines. Advanced monitoring ensures you get the right alerts and lineage helps you get to resolution faster.

Data Users

No more data discrepancies. Sifflet ensures the highest levels of data quality. Your teams can make the best possible decisions for your company, unlocking new levels of performance that help you compete in the age of AI.

Sifflet’s AI Helps Us Focus on What Moves the Business

What impressed us most about Sifflet’s AI-native approach is how seamlessly it adapts to our data landscape — without needing constant tuning. The system learns patterns across our workflows and flags what matters, not just what’s noisy. It’s made our team faster and more focused, especially as we scale analytics across the business.

Simoh-Mohamed Labdoui
Head of Data
"Enabler of Cross Platform Data Storytelling"

"Sifflet has been a game-changer for our organization, providing full visibility of data lineage across multiple repositories and platforms. The ability to connect to various data sources ensures observability regardless of the platform, and the clean, intuitive UI makes setup effortless, even when uploading dbt manifest files via the API. Their documentation is concise and easy to follow, and their team's communication has been outstanding—quickly addressing issues, keeping us informed, and incorporating feedback. "

Callum O'Connor
Senior Analytics Engineer, The Adaptavist
"Building Harmony Between Data and Business With Sifflet"

"Sifflet serves as our key enabler in fostering a harmonious relationship with business teams. By proactively identifying and addressing potential issues before they escalate, we can shift the focus of our interactions from troubleshooting to driving meaningful value. This approach not only enhances collaboration but also ensures that our efforts are aligned with creating impactful outcomes for the organization."

Sophie Gallay
Data & Analytics Director, Etam
" Sifflet empowers our teams through Centralized Data Visibility"

"Having the visibility of our DBT transformations combined with full end-to-end data lineage in one central place in Sifflet is so powerful for giving our data teams confidence in our data, helping to diagnose data quality issues and unlocking an effective data mesh for us at BBC Studios"

Ross Gaskell
Software engineering manager, BBC Studios
"Sifflet allows us to find and trust our data"

"Sifflet has transformed our data observability management at Carrefour Links. Thanks to Sifflet's proactive monitoring, we can identify and resolve potential issues before they impact our operations. Additionally, the simplified access to data enables our teams to collaborate more effectively."

Mehdi Labassi
CTO, Carrefour Links
"A core component of our data strategy and transformation"

"Using Sifflet has helped us move much more quickly because we no longer experience the pain of constantly going back and fixing issues two, three, or four times."

Sami Rahman
Director of Data, Hypebeast

Frequently asked questions

How does Flow Stopper support root cause analysis and incident prevention?
Flow Stopper enables early anomaly detection and integrates with your orchestrator to halt execution when issues are found. This makes it easier to perform root cause analysis before problems escalate and helps prevent incidents that could affect business-critical dashboards or KPIs.
What makes Carrefour’s approach to observability scalable and effective?
Carrefour’s approach combines no-code self-service tools with as-code automation, making it easy for both technical and non-technical users to adopt. This balance, along with incremental implementation and cultural emphasis on data quality, supports scalable observability across the organization.
Why is standardization important when scaling dbt, and how does Sifflet support it?
Standardization is key to maintaining control as your dbt project grows. Sifflet supports this by centralizing metadata and enabling compliance monitoring through features like data contracts enforcement and asset tagging. This ensures consistency, improves data governance, and reduces the risk of data drift or unmonitored critical assets.
What are the main challenges of implementing Data as a Product?
Some key challenges include ensuring data privacy and security, maintaining strong data governance, and investing in data optimization. These areas require robust monitoring and compliance tools. Leveraging an observability platform can help address these issues by providing visibility into data lineage, quality, and pipeline performance.
How does Sifflet help with data freshness monitoring?
At Sifflet, we offer a powerful Freshness Monitor that tracks when your data arrives and alerts you if it's missing or delayed. Whether you're working with batch or streaming pipelines, our observability platform makes it easy to stay on top of data freshness and ensure your analytics stay accurate and timely.
Who should be the first hire on a new data team?
If you're just starting out, look for someone with 'Full Data Stack' capabilities, like a Data Analyst with strong SQL and business acumen or a Data Engineer with analytics skills. This person can work closely with other teams to build initial pipelines and help shape your data platform. As your needs evolve, you can grow your team with more specialized roles.
Why is data freshness so important for data reliability?
Great question! Data freshness is a key part of data reliability because decisions are only as good as the data they're based on. If your data is outdated or delayed, it can lead to flawed insights and missed opportunities. That's why data freshness checks are a foundational element of any strong data observability strategy.
How does Sifflet support data governance at scale?
Sifflet supports scalable data governance by letting you tag declared assets, assign owners, and classify sensitive data like PII. This ensures compliance with regulations and improves collaboration across teams using a centralized observability platform.
Still have questions?

More Data. Less Chaos.

If you want a smoother running stack,
let’s talk about what Sifflet can do for you.