Monitor Your %%Entire%% Stack Automatically.
AI-powered monitoring that scales beyond manual rules, with context for fast diagnosis.
Monitoring That %%Adapts%% Without Constant Tuning
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.
"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. "
"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."
"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"
"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."
"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."
Continuous Monitoring
With Context Built In
Automate Monitoring Coverage
Sifflet recommends the right monitors based on risk, change frequency, and downstream impact, no manual rules required.
Detect Anomalies Early
Catch freshness, volume, schema, and distribution issues across pipelines and dashboards before they affect the business.
Keep Coverage Current
Monitoring adapts automatically as your stack changes, so blind spots don’t creep in over time.
Investigate Issues in Seconds, Not Hours.
Powered by AI Agents
Understand the Alert Instantly
See exactly what triggered the anomaly - the asset involved, what changed, and which downstream data is affected - without digging through logs or dashboards.
Explore the Signals Behind the Issue
Get a complete view of the metrics, patterns, and trends that led to the alert - freshness, volume, schema, drift, and more - enriched with the context you need to understand what actually went wrong.
Identify the Root Cause Fast
Trace the full chain of events to see what changed upstream, which assets depend on it, and where the break originated - making it easy to pinpoint the source and act quickly.
“ Sifflet’s AI Helps Us Focus on What Moves the Business ”
Stop %%Issues%% Before Your Stakeholders Ever Notice.
Sifflet monitors your data estate end-to-end, detects anomalies early, and helps your team pinpoint root cause fast so they can keep dashboards, models, and pipelines stay reliable as you scale.
-p-500.png)
