Make Data %%Observability%% Everyone’s Business

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

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.

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.

TRACEABLE

Improve productivity and collaboration between engineers and data consumers

For everyone, working with and finding data becomes intuitive with a simple and automated UI, data discovery is simplified with a data catalog, and it is easy to connect with coding workflows.

Sifflet dashboard features overview
Sifflet dashboard data monitoring
Data Lineage

Troubleshoot

When data breaks, take charge. Use Sifflet’s robust tracing capabilities to map your data upstream, downstream and across data layers. You’ll gain insight into your data across the entire lifecycle and see rapid improvements to data quality that benefit the entire company.

Sifllet dashboard data quality monitoring
Data quality monitoring

Monitor

Monitor it all. And more.  Sifflet offers both out of the box and custom monitoring capability, so your teams can keep an eye on assets you know need observation…and even those you don’t.  Our AI optimizes your coverage and minimizes noise, getting smarter as it goes.  Your data’s reliability is reinforced, helping to grow confidence in your numbers. Now that’s performance. 

Built for %%Everyone%%

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

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.

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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.

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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.

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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
Still have a question in mind ?
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Frequently asked questions

Can Sifflet help me monitor data drift and anomalies beyond what dbt offers?
Absolutely! While dbt is fantastic for defining tests, Sifflet takes it further with advanced data drift detection and anomaly detection. Our platform uses intelligent monitoring templates that adapt to your data’s behavior, so you can spot unexpected changes like missing rows or unusual values without setting manual thresholds.
When should organizations start thinking about data quality and observability?
The earlier, the better. Building good habits like CI/CD, code reviews, and clear documentation from the start helps prevent data issues down the line. Implementing telemetry instrumentation and automated data validation rules early on can significantly improve data pipeline monitoring and support long-term SLA compliance.
How does Sifflet help with root cause analysis when something breaks in a data pipeline?
When a data issue arises, Sifflet gives you the context you need to act fast. Our observability platform connects the dots across your data stack—tracking lineage, surfacing schema changes, and highlighting impacted assets. That makes root cause analysis much easier, whether you're dealing with ingestion latency or a failed transformation job. Plus, our AI helps explain anomalies in plain language.
Can I monitor the health of my Firebolt tables in real time with Sifflet?
Absolutely! With Sifflet's observability platform, you can view the health status of your Firebolt tables in real time. This allows for proactive data pipeline monitoring and helps ensure SLA compliance across your analytics workflows.
Can Sifflet help reduce false positives during holidays or special events?
Absolutely! We know that data patterns can shift during holidays or unique business dates. That’s why Sifflet now lets you exclude these dates from alerts by selecting from common calendars or customizing your own. This helps reduce alert fatigue and improves the accuracy of anomaly detection across your data pipelines.
What should a solid data quality monitoring framework include?
A strong data quality monitoring framework should be scalable, rule-based and powered by AI for anomaly detection. It should support multiple data sources and provide actionable insights, not just alerts. Tools that enable data drift detection, schema validation and real-time alerts can make a huge difference in maintaining data integrity across your pipelines.
What role does data governance play in a data observability platform?
Data governance is a core component of any robust data observability solution. Look for platforms that offer features like audit logging, access controls, and encryption. These capabilities help ensure your organization stays compliant with regulations like GDPR, while also protecting sensitive data and maintaining transparency across teams.
Is data governance more about culture or tools?
It's a mix of both, but culture plays a big role. As Dan Power puts it, 'culture eats strategy for breakfast.' Even the best observability tools won't succeed without enterprise-wide data literacy and buy-in. That’s why training, user-friendly platforms, and fostering collaboration are just as important as the technology stack you choose.

More data. %%Less Chaos.%%

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

Contact Us