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.

Dynex Capital
Euronext
Dailymotion
Saint-Gobain
ShopBack
Servier
Penguin Random House
Adaptavist
Mollie
Hypebeast
Deuna
BBC Studios
Carrefour
Etam
Auchan

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
Dynex Capital
Euronext
Dailymotion
Saint-Gobain
ShopBack
Servier
Penguin Random House
Adaptavist
Mollie
Hypebeast
Deuna
BBC Studios
Carrefour
Etam
Auchan
Still have a question in mind ?
Contact Us

Frequently asked questions

How is data volume different from data variety?
Great question! Data volume is about how much data you're receiving, while data variety refers to the different types and formats of data sources. For example, a sudden drop in appointment data is a volume issue, while a new file format causing schema mismatches is a variety issue. Observability tools help you monitor both dimensions to maintain healthy pipelines.
What kind of integrations does Sifflet offer for data pipeline monitoring?
Sifflet integrates with cloud data warehouses like Snowflake, Redshift, and BigQuery, as well as tools like dbt, Airflow, Kafka, and Tableau. These integrations support comprehensive data pipeline monitoring and ensure observability tools are embedded across your entire stack.
What kind of real-time alerts can I expect with Sifflet and dbt together?
With Sifflet and dbt working together, you get real-time alerts delivered straight to your favorite tools like Slack, Microsoft Teams, or email. Whether a dbt test fails or a data anomaly is detected, your team will be notified immediately, helping you respond quickly and maintain data quality monitoring at all times.
Why is agentic observability critical for modern data environments?
Modern data environments are complex, distributed, and constantly evolving. Agentic observability is essential because it brings AI-powered automation to the forefront, enabling proactive monitoring, anomaly detection, and dynamic thresholding. It’s a scalable approach to managing data drift detection, pipeline health, and incident response in real time.
Can Sifflet help with data pipeline monitoring in lakehouse environments?
Absolutely! Sifflet offers comprehensive data pipeline monitoring by focusing on metadata-driven signals. It monitors table health, detects missed compactions, and alerts you about retention risks, helping you maintain performance and governance in your lakehouse architecture.
Can Sifflet integrate with our existing data tools and platforms?
Absolutely! Sifflet is designed to integrate seamlessly with your current stack. We support a wide range of tools including Airflow, Snowflake, AWS Glue, and more. Our goal is to provide complete pipeline orchestration visibility and data freshness checks, all from one intuitive interface.
When should I consider using a point solution like Anomalo or Bigeye instead of a full observability platform?
If your team has a narrow focus on anomaly detection or prefers a SQL-first, hands-on approach to monitoring, tools like Anomalo or Bigeye can be great fits. However, for broader needs like data governance, business impact analysis, and cross-functional collaboration, a platform like Sifflet offers more comprehensive data observability.
Why is data observability becoming a business imperative in industries like finance and logistics?
In sectors like financial services, insurance, and logistics, data reliability isn't just a technical concern, it's a compliance and operational necessity. A single data incident can lead to regulatory risks or business disruption. That's why data observability platforms like Sifflet are being adopted to ensure data quality, monitor pipelines in real time, and maintain SLA compliance.

More data. %%Less Chaos.%%

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

Contact Us