Product

Data Security

%%Simply%% Secure

Sifflet makes no compromises when it comes to ensuring your security, risk mitigation, and compliance.

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Least Privilege Policies

Sifflet helps you manage who can access what data. It features RBAC principles to grant or restrict access based on a user’s role in the organization, rather than managing individual permissions.

A No Data Storage Approach

Our approach eliminates persistent data storage, with transient data handling and ephemeral computing principles.

State of the Art Isolation

Sifflet uses single tenancy architecture, so each and every client benefits from a dedicated and isolated instance of our tooling, infrastructure, and associated resources.

ENSURE

Product Security

Sifflet gives you peace of mind with tools to keep access to your environment protected.

SaaS or self-hosted deployment
Cross-IdP SSO support
RBAC

ISOLATE

Platform Security

Security at the platform level to keep each and every client safe.

Single tenancy architecture for state of the art isolation
No data alteration and least privilege policy
No data storage approach

PROTECT

Compliance Certifications

Your data’s sensitive. Sifflet is certified compliant across a range of standards.

SOC 2
ISO 27001
GDPR
HIPAA

Reinforced %%Reliability%%

Sifflet’s monitoring features reinforce data reliability for all users, so business can deliver.

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Data Users

Enhance customer trust with tools that secure data and help your business align with regulatory and compliance requirements.

Data Engineers

Keep specific data pipelines and storage systems confidential and protect critical data assets from manipulation.

Data Leaders

Avoid legal issues, financial penalties and reputational damage associated with data mishandling, or unauthorized data access and breaches.

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sifflet a guide to assessing your need for a data observability

Insights

A Guide to Assessing your Need for Data Observability

Product

How Sifflet keeps your data safe

Product

Data quality for all - Un-siloed data quality

Need %%strong%% data protection?

Benefit from peace of mind that your sensitive data is safe and your business mitigates risk by remaining compliant.

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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

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Frequently asked questions

What’s coming next for dbt integration in Sifflet?

We’re just getting started! Soon, you’ll be able to monitor dbt run performance and resource utilization, define monitors in your dbt YAML files, and use custom metadata even more dynamically. These updates will further enhance your cloud data observability and make your workflows even more efficient.

How does Sifflet help detect and prevent data drift in AI models?

Sifflet is designed to monitor subtle changes in data distributions, which is key for data drift detection. This helps teams catch shifts in data that could negatively impact AI model performance. By continuously analyzing incoming data and comparing it to historical patterns, Sifflet ensures your models stay aligned with the most relevant and reliable inputs.

What role does data lineage tracking play in storage observability?

Data lineage tracking is essential for understanding how data flows from storage to dashboards. When something breaks, Sifflet helps you trace it back to the storage layer, whether it's a corrupted file in S3 or a schema drift in MongoDB. This visibility is critical for root cause analysis and ensuring data reliability across your pipelines.

Why should companies invest in data pipeline monitoring?

Data pipeline monitoring helps teams stay on top of ingestion latency, schema changes, and unexpected drops in data freshness. Without it, issues can go unnoticed and lead to broken dashboards or faulty decisions. With tools like Sifflet, you can set up real-time alerts and reduce downtime through proactive monitoring.

How does data observability support AI and machine learning initiatives?

AI models are only as good as the data they’re trained on. With data observability, you can ensure data quality, detect data drift, and enforce validation rules, all of which are critical for reliable AI outcomes. Sifflet helps you maintain trust in your data so you can confidently scale your ML and predictive analytics efforts.

Can non-technical users benefit from Sifflet’s data observability platform?

Absolutely. Sifflet is designed to be accessible to everyone. With an intuitive UI and our AI Assistant, even non-technical users can set up data quality monitors, track real-time metrics, and contribute to data governance without writing a line of code.

What makes Carrefour’s approach to observability scalable and effective?

Carrefour’s approach combines no-code self-service tools with as-code automation, making it easy for both technical and non-technical users to adopt. This balance, along with incremental implementation and cultural emphasis on data quality, supports scalable observability across the organization.

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.

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