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

Can observability platforms help AI systems make better decisions with data?

Absolutely. AI systems need more than just schemas—they need context. Observability platforms like Sifflet provide machine-readable trust signals, data freshness checks, and reliability scores through APIs. This allows autonomous agents to assess data quality in real time and make smarter decisions without relying on outdated documentation.

Can MCP help with data pipeline monitoring and incident response?

Absolutely! MCP allows LLMs to remember past interactions and call diagnostic tools, which is a game-changer for data pipeline monitoring. It supports multi-turn conversations and structured tool use, making incident response faster and more contextual. This means less time spent digging through logs and more time resolving issues efficiently.

What is data observability and why is it important?

Data observability is the ability to monitor, understand, and troubleshoot data systems using real-time metrics and contextual insights. It's important because it helps teams detect and resolve issues quickly, ensuring data reliability and reducing the risk of bad data impacting business decisions.

How can data observability help companies stay GDPR compliant?

Great question! Data observability plays a key role in GDPR compliance by giving teams real-time visibility into where personal data lives, how it's being used, and whether it's being processed according to user consent. With an observability platform in place, you can track data lineage, monitor data quality, and quickly respond to deletion or access requests in a compliant way.

Why is data observability important in a modern data stack?

Data observability is crucial because it ensures your data is reliable, trustworthy, and ready for decision-making. It sits at the top of the modern data stack and helps teams detect issues like data drift, schema changes, or freshness problems before they impact downstream analytics. A strong observability platform like Sifflet gives you peace of mind and helps maintain data quality across all layers.

What are the main challenges of implementing Data as a Product?

Some key challenges include ensuring data privacy and security, maintaining strong data governance, and investing in data optimization. These areas require robust monitoring and compliance tools. Leveraging an observability platform can help address these issues by providing visibility into data lineage, quality, and pipeline performance.

What is data governance and why does it matter for modern businesses?

Data governance is a framework of policies, roles, and processes that ensure data is accurate, secure, and used responsibly across an organization. It brings clarity and accountability to data management, helping teams trust the data they use, stay compliant with regulations, and make confident decisions. When paired with data observability tools, governance ensures data remains reliable and actionable at scale.

What exactly is data freshness, and why does it matter so much in data observability?

Data freshness refers to how current your data is relative to the real-world events it's meant to represent. In data observability, it's one of the most critical metrics because even accurate data can lead to poor decisions if it's outdated. Whether you're monitoring financial trades or patient records, stale data can have serious business consequences.

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