Product

Show Your %%Data Stack%% Who’s Boss.

Sifflet’s platform is powered by AI to tackle the sheer volume and complexity of the modern data stack.

Talk to an Expert

Launch Product Tour

Augmented Assistance

Let AI help you speed things up. Sifflet is designed to reduce tedious tasks - like generating metadata descriptions or correcting SQL - with the click of a button.

No Coding Skills Required

Not an engineer? Not a problem. Describe what kind of monitors you’d like and Sifflet takes care of the rest.

Smart Alerts

Sifflet uses AI to optimize monitoring coverage and avoid alert fatigue by sending you the right alerts at the right time.

ADAPT

%%Dynamic%% Monitors

Monitors that get smarter as they go.

AI that creates monitors based on your prompts
Monitoring that learns from historical and on-going data
Detects anomalies in real time, adapts to trends, and sends meaningful alerts

ASSIST

Building Rich %%Metadata%%

Say goodbye to creating metadata manually.

AI-generated column and asset descriptions.
Automatic classification for the data in your fields.

%%Easy%% Monitor Creation

Create monitors, monitor names and descriptions effortlessly.

Monitor configuration, title and description suggestions.
SQL correction.
Regex suggestions
Monitor of Monitoring Accuracy (MoMA) suggestions

Tame Your Stack. %%Scale Your Smarts.%%

Sifflet’s AI-powered features help you show your stack who’s boss. Augment your team’s capabilities and make data observability everyone’s business.

Get in touch

Data Users

Thanks to AI, there’s no need to wait for the data engineering team to adapt, create or fix a monitor. Your monitors can also adapt to changes in seasonal trends.

Data Engineers

Sifflet’s AI helps reduce manual work on tedious, repetitive tasks and gives your data users self-serve tools instead of requiring engineering time.

Data Leaders

AI features that make your data engineers more efficient and your data users better able to take ownership of their data.

Looking for more?

7 Reasons for Data Observability within AI-Powered Organizations

Sifflet AI Assistant - Automating your data observability at scale

AI and Data Management

Scale isn't so %%scary%%.

Sifflet’s AI-powered features help you wrangle your stack, even as it scales. Augment your team's capabilities today to make data observability everyone’s business.

Talk to our Experts

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 ?

Frequently asked questions

What role does data ownership play in data quality monitoring?

Clear data ownership is a game changer for data quality monitoring. When each data product has a defined owner, it’s easier to resolve issues quickly, collaborate across teams, and build a strong data culture that values accountability and trust.

What kinds of alerts can trigger incidents in ServiceNow through Sifflet?

You can trigger incidents from any Sifflet alert, including data freshness checks, schema changes, and pipeline failures. This makes it easier to maintain SLA compliance and improve overall data reliability across your observability platform.

What can I expect to learn from Sifflet’s session on cataloging and monitoring data assets?

Our Head of Product, Martin Zerbib, will walk you through how Sifflet enables data lineage tracking, real-time metrics, and data profiling at scale. You’ll get a sneak peek at our roadmap and see how we’re making data more accessible and reliable for teams of all sizes.

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.

Where can I find Sifflet at Big Data LDN 2024?

You can find the Sifflet team at Booth Y640 during Big Data LDN on September 18-19. Stop by to learn more about our data observability platform and how we’re helping organizations like the BBC and Penguin Random House improve their data reliability.

What strategies can help smaller data teams stay productive and happy?

For smaller teams, simplicity and clarity are key. Implementing lightweight data observability dashboards and using tools that support real-time alerts and Slack notifications can help them stay agile without feeling overwhelmed. Also, defining clear roles and giving access to self-service tools boosts autonomy and satisfaction.

What makes Sifflet a more inclusive data observability platform compared to Monte Carlo?

Sifflet is designed for both technical and non-technical users, offering no-code monitors, natural-language setup, and cross-persona alerts. This means analysts, data scientists, and executives can all engage with data quality monitoring without needing engineering support, making it a truly inclusive observability platform.

What are some best practices for ensuring data quality during transformation?

To ensure high data quality during transformation, start with strong data profiling and cleaning steps, then use mapping and validation rules to align with business logic. Incorporating data lineage tracking and anomaly detection also helps maintain integrity. Observability tools like Sifflet make it easier to enforce these practices and continuously monitor for data drift or schema changes that could affect your pipeline.

Read all FAQs