At Sifflet,
Data Means Business.

Data drives every strategic decision, guides innovation, and powers transformation. But how do companies ensure their data is reliable? How can they trust the insights that guide critical business choices? How do they turn raw information into actionable intelligence, high-performing products, and superior strategies? Enter Sifflet.

Who We Are

We are a data observability platform.
We offer end-to-end oversight into the entire data stack, helping teams to uncover, prevent and overcome the technical and organizational obstacles that get in the way of better quality, more reliable data.

Our Mission

We help companies see data breakthroughs. Sifflet delivers smoother running data stacks by providing detailed oversight and solutions that reduce data breaks, improve team alignment and operations, and build confidence in the numbers. The result? Superior insights, value and products from data.

Meet our Executive team

Sifflet was built by a data-obsessed team for
data-obsessed teams.

We’re Hiring!

Chief Executive Officer

Salma Bakouk

Before founding Sifflet, Salma worked in quantitative sales & trading at Goldman Sachs, where she saw firsthand how unreliable data could undermine even the most sophisticated models. She holds two master’s degrees in Applied Mathematics and Computer Science from École Centrale Paris. Named among Europe’s Top 100 Women in Tech, Salma is a frequent speaker at leading industry events including Gartner D&A Summit and Big Data LDN. Outside of work, she loves running mountain trails, discovering new cities, and spending time with her dog always chasing the same clarity and balance she strives to bring to data.

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Frequently asked questions

How does Sifflet use AI to enhance data observability?

Sifflet uses AI not just for buzzwords, but to genuinely improve your workflows. From AI-powered metadata generation to dynamic thresholding and intelligent anomaly detection, Sifflet helps teams automate data quality monitoring and make faster, smarter decisions based on real-time insights.

How does Kubernetes help with container orchestration?

Kubernetes makes it easier to manage large-scale containerized applications by automating deployment, scaling, and operations. It's a powerful observability tool that supports real-time metrics collection, resource utilization tracking, and pipeline orchestration visibility, helping teams stay on top of their data pipelines.

How does Sifflet support AI readiness within enterprises?

Sifflet reinforces AI-powered capabilities through features like data freshness checks, data profiling, and anomaly scoring. These tools ensure your data is accurate and trustworthy, which is crucial for training reliable machine learning models and enabling predictive analytics monitoring.

How does Sifflet make setting up data quality monitoring easier?

Great question! With the launch of Data-Quality-as-Code v2, Sifflet has made it much easier to create and manage monitors at scale. Whether you prefer working programmatically or through the UI, our platform now offers smoother workflows and standardized threshold settings for more intuitive data quality monitoring.

What is data observability and why is it important for modern data teams?

Data observability is the practice of monitoring data as it moves through your pipelines to detect, understand, and resolve issues proactively. It’s crucial because it helps data teams ensure data reliability, improve decision-making, and reduce the time spent firefighting data issues. With the growing complexity of data systems, having a robust observability platform is key to maintaining trust in your data.

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.

What kinds of data does Shippeo monitor to support real-time metrics?

Shippeo tracks critical operational data like order volume, GPS positions, and platform activity. With Sifflet, they monitor ingestion latency and data freshness to ensure that metrics powering dashboards and customer reports are always up to date.

How can I measure whether my data is trustworthy?

Great question! To measure data quality, you can track key metrics like accuracy, completeness, consistency, relevance, and freshness. These indicators help you evaluate the health of your data and are often part of a broader data observability strategy that ensures your data is reliable and ready for business use.

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Want to join the team?

We're seeking driven individuals eager to roll up their sleeves and help make data observability everyone's business.

Join Sifflet

At Sifflet, Data Means Business.