The Control Plane for %%Data and AI%%

We catch data issues before they reach the business, show exactly why they happened, and how to fix them. So the data behind every decision is one you can trust.

The premier %%virtual summit%% on data reliability, observability, and the future of trustworthy AI.

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.

Your pipelines are monitored. Your alerts are firing. %%So why does bad data keep reaching the business?%%

Detection is table stakes. What matters is what happens next: why it broke, what it affects, and how to fix it.

Know What Actually Matters

Not all alerts are equal. Sifflet enriches every issue with lineage, downstream usage, and ownership — so you stop treating schema drift and a broken exec dashboard the same way. Focus on what has real business consequences.

Stop Playing Detective

When something breaks, the context you need is already there: upstream lineage, recent schema changes, historical behavior. The root cause you'd spend hours hunting, surfaced in minutes.

One Control Layer Across Your Full Stack

Incidents don't respect tool boundaries. Sifflet covers the whole chain — warehouses, orchestrators, BI — so nothing falls through the gap between Snowflake and the dashboard your CFO opens on Monday morning.

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 features overview
Data Lineage

Troubleshoot

When data breaks, trace it. Map any issue upstream, downstream, and across layers — field by field. Know exactly where a number came from, what it affects, and how to fix it. A lineage gap is a trust gap. Sifflet closes it.

Data quality monitoring

Monitor

Monitor everything. Miss nothing. Out-of-the-box and custom monitoring across every asset — including the ones you didn't know to watch. AI reduces noise as your stack grows, so your team stays focused on signals that matter, not the ones that don't.

Data reliability is a team sport

The right view for everyone in the buying center: the people who build it, the people who govern it, and the people who depend on it.

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

What kind of metadata can I see for a Fivetran connector in Sifflet?
When you click on a Fivetran connector node in the lineage, you’ll see key metadata like source and destination, sync frequency, current status, and the timestamp of the latest sync. This complements Sifflet’s existing metadata like owner and last refresh for complete context.
Why is a user-friendly interface important in an observability tool?
A user-friendly interface boosts adoption across teams and makes it easier to navigate complex datasets. For observability tools, especially those focused on data cataloging and data discovery, a clean UI enables faster insights and more efficient collaboration.
How does Sifflet support proactive data pipeline monitoring?
Sifflet’s observability platform offers proactive data pipeline monitoring through extensive monitoring tools, real-time alerts, and historical performance insights. These features help your team stay ahead of issues and ensure your data pipelines are always delivering high-quality, reliable data.
What is the 'Metadata Ceiling' mentioned in the Datadog review?
The 'Metadata Ceiling' refers to the limitations of infrastructure-first observability tools like Datadog when it comes to understanding the actual content and business impact of data. While Datadog excels at monitoring pipeline health and system performance, it lacks the deep data observability features required to catch issues like null values in critical reports or corrupted inputs in AI models. For full visibility into data quality and business relevance, a specialized observability platform like Sifflet is often a better fit.
Can Sifflet help with root cause analysis when data issues arise?
Absolutely! Sifflet’s field-level data lineage tracking lets you trace data issues from BI dashboards all the way back to source systems. Its AI agent, Sage, even recalls past incidents to suggest likely causes, making root cause analysis faster and more accurate for data engineers and analysts alike.
What exactly is the modern data stack, and why is it so popular now?
The modern data stack is a collection of cloud-native tools that help organizations transform raw data into actionable insights. It's popular because it simplifies data infrastructure, supports scalability, and enables faster, more accessible analytics across teams. With tools like Snowflake, dbt, and Airflow, teams can build robust pipelines while maintaining visibility through data observability platforms like Sifflet.
How can I prevent schema changes from breaking my data pipelines?
You can prevent schema-related breakages by using data observability tools that offer real-time schema drift detection and alerting. These tools help you catch changes early, validate against data contracts, and maintain SLA compliance across your data pipelines.
Is this feature part of Sifflet’s larger observability platform?
Yes, dbt Impact Analysis is a key addition to Sifflet’s observability platform. It integrates seamlessly into your GitHub or GitLab workflows and complements other features like data lineage tracking and data quality monitoring to provide holistic data observability.

More data. %%Less Chaos.%%

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

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