Make Data Observability Everyone’s Business

Sifflet is an AI-native data observability platform built for data teams with business users in mind. 

Make Data Observability Everyone’s Business
Trusted by Leading Companies

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.
 g2 labels
Join the ranks of happy customers who’ve made Sifflet a G2 leader, trusted for its innovation and impact
sifflet platform graph
Stay ahead of issues with real-time alerts that keep you informed and in control of your data health
Sifflet platform tags
Organize, discover, and leverage your data assets effortlessly with a smart, searchable catalog built for modern teams.
Sifflet platform code extract
Harness the power of AI-driven suggestions to improve efficiency, accuracy, and decision-making across your workflows.
sifflet work team
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

Can Subdomains help with data governance and compliance requirements like GDPR or HIPAA?
Absolutely. With granular access control at the subdomain level, you can restrict sensitive data access to only the right people. This makes it much easier to meet data governance and compliance standards such as GDPR, HIPAA, and SOC 2, especially in highly regulated industries.
Why is data observability important during the data integration process?
Data observability is key during data integration because it helps detect issues like schema changes or broken APIs early on. Without it, bad data can flow downstream, impacting analytics and decision-making. At Sifflet, we believe observability should start at the source to ensure data reliability across the whole pipeline.
Why might Metaplane fall short for teams with complex data environments?
Metaplane is great for small teams and dbt-centric workflows, but it lacks depth in areas like infrastructure observability, field-level lineage, and ML model monitoring. As your stack grows to include streaming data, hybrid cloud, or multiple orchestration tools, you’ll need a more robust observability platform to maintain data quality and SLA compliance.
How does Sifflet use AI to improve data classification?
Sifflet leverages machine learning to provide AI Suggestions for classification tags, helping teams automatically identify and label key data characteristics like PII or low cardinality. This not only streamlines data management but also enhances data quality monitoring by reducing manual effort and human error.
Can container-based environments improve incident response for data teams?
Absolutely. Containerized environments paired with observability tools like Kubernetes and Prometheus for data enable faster incident detection and response. Features like real-time alerts, dynamic thresholding, and on-call management workflows make it easier to maintain healthy pipelines and reduce downtime.
What role did data quality monitoring play in jobvalley’s success?
Data quality monitoring was key to jobvalley’s success. By using Sifflet’s data observability tools, they were able to validate the accuracy of business-critical tables, helping build trust in their data and supporting confident, data-driven decision-making.
What can I expect from Sifflet at Big Data Paris 2024?
We're so excited to welcome you at Booth #D15 on October 15 and 16! You’ll get to experience live demos of our latest data observability features, hear real client stories like Saint-Gobain’s, and explore how Sifflet helps improve data reliability and streamline data pipeline monitoring.
What is “data-quality-as-code”?

Data-quality-as-code (DQaC) allows you to programmatically define and enforce data quality rules using code. This ensures consistency, scalability, and better integration with CI/CD pipelines. Read more here to find out how to leverage it within Sifflet

Still have questions?

More Data. Less Chaos.

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