From Detection to %%Decision%%

Sifflet is the business-aware data observability platform that connects data quality issues to real business impact.
Know exactly what to fix first, and why.

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 every incident still feel like a scramble?

You don't have a detection problem. You have a decision problem.

Prioritize by Business Risk, Not Just Technical Severity

Treating all anomalies equally creates alert fatigue. Sifflet answers "Does this matter, and to whom?" by enriching every data quality check with lineage, downstream BI usage, and ownership. Focus your engineering effort on incidents with real business consequences.

Faster Triage Through Context-Enriched Investigation

Stop playing detective. When an incident occurs, Sifflet centralizes the context you usually have to hunt for: upstream and downstream lineage, recent schema changes, and historical behavior. Cut MTTR from hours to minutes.

One Reliability Layer, End-to-End

Business impact shows up downstream. Sifflet provides a unified observability layer across your entire modern data stack, from warehouses (Snowflake, BigQuery) and orchestrators (Airflow, dbt) directly to your BI platforms (Tableau, Looker).

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. 

Data reliability is a team sport

Tailored context for the people who build, govern, and consume 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

What role does data lineage play in incident management and alerting?
Data lineage provides visibility into data dependencies, which helps teams assign, prioritize, and resolve alerts more effectively. In an observability platform like Sifflet, this means faster incident response, better alert correlation, and improved on-call management workflows.
How does Sifflet enhance Apache Airflow for data teams?
Sifflet's integration with Apache Airflow brings powerful data observability features directly into your orchestration workflows. It helps data teams monitor DAG run statuses, understand downstream dependencies, and apply data quality monitoring to catch issues early, ensuring data reliability across the stack.
Can agentic observability help reduce alert fatigue for data teams?
Absolutely. One of the biggest advantages of agentic observability is alert fatigue reduction. Instead of flooding teams with scattered alerts, agents like Sage consolidate related issues into a single, coherent narrative. This focused approach allows teams to prioritize what matters most and respond faster, improving both efficiency and data observability.
What makes data observability different from traditional monitoring tools?
Traditional monitoring tools focus on infrastructure and application performance, while data observability digs into the health and trustworthiness of your data itself. At Sifflet, we combine metadata monitoring, data profiling, and log analysis to provide deep insights into pipeline health, data freshness checks, and anomaly detection. It's about ensuring your data is accurate, timely, and reliable across the entire stack.
Why is data observability essential for building trusted data products?
Great question! Data observability is key because it helps ensure your data is reliable, transparent, and consistent. When you proactively monitor your data with an observability platform like Sifflet, you can catch issues early, maintain trust with your data consumers, and keep your data products running smoothly.
Can Sifflet monitor data quality in real-time?
Absolutely! Sifflet supports real-time metrics and data quality monitoring across your pipelines. Our AI agents continuously track data freshness, schema changes, and anomalies, so you’re alerted the moment something looks off. It’s like having a 24/7 data guardian that ensures your business decisions are based on accurate and timely information.
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.
What’s the role of an observability platform in scaling data trust?
An observability platform helps scale data trust by providing real-time metrics, automated anomaly detection, and data lineage tracking. It gives teams visibility into every layer of the data pipeline, so issues can be caught before they impact business decisions. When observability is baked into your stack, trust becomes a natural part of the system.

More data. %%Less Chaos.%%

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

Contact Us