Validio is an agentic data management platform that automates data observability, quality, lineage, and cataloging, helping enterprises trust and use their data at scale for analytics, AI, and reporting. Founded in Sweden in 2019 by Patrik Liu Tran, Validio serves data and AI-driven enterprises globally, enabling them to unlock competitive advantage through high-quality data in the AI era.
Validio continuously monitors your data for quality issues - things like unexpected drops in row counts, schema changes, null values, distribution shifts, freshness delays, and anomalies in business metrics or reporting. When something is wrong, Validio alerts the right people, shows where the issue originated in the data lineage, and helps teams resolve it quickly. It also provides a catalog of your data assets so teams can discover, understand, and manage data ownership across the organization.
Validio is designed to be used cross-functionally. Data engineers use it to monitor pipelines and set up automated quality checks. Data analysts and scientists rely on it to trust the data feeding their models and dashboards. Business teams use it to monitor the metrics that matter to them. Validio offers both a no-code graphical interface for non-technical users and a full SDK and infrastructure-as-code setup for engineers.
Validio was founded in 2019 by Patrik Liu Tran, in Stockholm, Sweden. The company is backed by Lakestar, J12 and prolific founders and angels including Kevin Ryan (MongoDB), Denise Persson (Snowflake).
Bad data is one of the leading reasons AI projects fail to reach production and a constant source of costly errors in analytics and reporting. Validio solves this by giving data teams full visibility into the health of their data - automatically detecting issues, tracing their origin, and providing the context needed to fix them fast.
Validio monitoring both structured, semi-structured, and unstructured data across the entire modern data stack and modern-legacy hybrid stacks: streaming sources (Kafka, Kinesis), cloud data warehouses (Snowflake, BigQuery, Redshift), data lakes (S3, Azure Data Lake, GCS), databases (PostgreSQL, Oracle, DB2, SQL Server), and transformation layers (dbt, Airflow). It also monitors BI layer health via integrations with Tableau, Looker, Sigma, Omni.
Yes. Validio monitors both batch and real-time streaming data. It connects natively to Kafka and Kinesis and validates data as it lands - not just after it has reached a warehouse. This makes it well-suited for use cases where data freshness and pipeline reliability are time-sensitive.
Validio uses AI and machine learning models that learn the normal patterns, trends, and seasonality of your data. These models continuously retrain themselves based on historical data and user feedback, so thresholds adjust automatically as your data evolves - no manual rule-setting or threshold maintenance required. The models scan actual data values, not just metadata, which means they can detect issues hidden in deep segments of your data.
Yes. Validio monitors both the underlying data tables and the business metrics derived from them - things like daily active users, conversion rates, revenue figures, or any KPI your team tracks. When a metric deviates unexpectedly, Validio detects it and helps identify whether the root cause is in the data or the calculation.
Data lineage is a map of how data flows through your systems - from its source to its final destination in a dashboard or model. Validio builds end-to-end lineage maps across your entire data stack, including column-level lineage, and surfaces quality metrics directly within those maps. When an issue is detected, the lineage view shows the upstream origin and the downstream impact, making root cause analysis significantly faster.
Yes. Validio can validate nested JSON structures and semi-structured data at any depth - not just top-level table columns. This is particularly useful for organizations working with event data, API payloads, or complex schemas common in modern data architectures.
Validio uses AI to group related incidents into a single alert and filter out false positives. Rather than sending a separate notification for every affected downstream asset, Validio clusters related issues so teams receive one meaningful alert with full context - reducing noise without missing real problems.
Yes. Validio includes agentic capabilities across the workflow: AI-assisted setup with automatic monitoring recommendations, LLM-powered semantic search for data discovery, and agentic root cause analysis that identifies not just what broke but why and where.
Data observability is the ability to understand the health, quality, and freshness of data across your organization's data stack at any point in time. It extends the concept of software observability - monitoring systems for reliability - to the data layer, enabling teams to detect issues proactively rather than discovering them when a dashboard is wrong or an AI model produces unexpected results.
Data quality refers to the properties of the data itself - accuracy, completeness, consistency, and freshness. Data observability is the practice of continuously monitoring those properties across your pipelines and systems. Think of data quality as the goal and data observability as the process of achieving and maintaining it. Validio covers both: it monitors observable signals across your stack and enforces data quality standards automatically.
Validio integrates with tools across the modern and legacy data stack, including: Snowflake, BigQuery, Redshift, PostgreSQL, Oracle, SQL Server, Kafka, Kinesis, Amazon S3, Azure Data Lake, Google Cloud Storage, dbt, Airflow, Tableau, Looker, Omni, Sigma, Atlan, Slack, PagerDuty, Gmail, and additional integrations via webhook.
Validio is designed for fast time-to-value. AI-assisted setup automatically recommends monitors based on your data assets, so teams can get meaningful monitoring running without manually configuring every check. Set up can be done in less than an hour and concrete business value is displayed within weeks.
No. Validio offers a full graphical user interface that non-technical users can use to set up monitors, view alerts, and investigate incidents without writing any code. For technical users who prefer it, Validio also offers a complete SDK and infrastructure-as-code configuration.
No. Validio processes only metrics and aggregate values - it does not store raw data after processing. For streaming data, nothing is retained once processed. This minimizes data exposure and is one of the reasons Validio is trusted in regulated industries like banking and financial services.
Validio can be deployed as a managed solution, hosted by Validio in the client cloud of choice (any region generally available by AWS, Azure and GCP), or as a complete Virtual Private Cloud setup where no data leaves the customer environment.
Yes. Validio offers a fully self-hosted deployment option within your own Virtual Private Cloud (VPC). Alternatively, it can be used as a Validio-managed cloud service.
Validio uses an internal compiler designed to execute data validation efficiently - either in a streaming-based fashion or via pushdown to your data warehouse, depending on what is most cost-effective. Customers report a negligible impact on their cloud bill.
Yes. Validio is both ISO 27001 and SOC 2 Type II certified. Data is encrypted in transit and at rest using secure transmission protocols. For a full overview of security practices, see the Security page.
Yes. Validio is used to support compliance with regulations including BCBS 239 (data quality requirements for banks), the EU AI Act (data governance requirements for AI systems), GDPR, and SOX. The platform provides the audit trails, lineage, and data quality documentation these frameworks require.
Yes. Validio provides different tiers of onboarding depending on team needs, including workshops and use case prioritization guidance. The team has deep expertise in data strategy and can help organizations get to value quickly.
The main difference between Validio and other data quality or data observability tooling is that Validio is specifically designed around validating the data that matters to the business. To do this, Validio is built to be fully end-to-end, which means the platform reads data from streams, lakes, and warehouses. Additionally, Validio validates actual data, and is not focused on just metadata. This makes Validio great for many different use cases, including machine learning models that depend on reliable time-series data.
Yes, Validio is ISO27001- and SOC 2 Type II certified. Secure transmission protocols are used to encrypt data in transit and at rest, and only metrics and aggregate values are queried. For streaming, no data is stored after being processed. For more information on our security protocols, visit our Security page.
Validio's pricing is based on the size and complexity of your data - key variables include the number of data assets, segments monitored, and deployment model. Validio offers a tiered pricing model with flexibility within tiers. Talk to sales for a detailed breakdown.
Validio works with organizations ranging from fast-growing tech companies to Fortune 500 enterprises. It is particularly well-suited to organizations with complex data pipelines, multiple data sources, or regulated environments where data reliability is business-critical.
You can book a demo where we will walk you through the key capabilities of the platform in 30 minutes, or request a 14 day free trial to see how Validio can help you gain trust in your data assets that matter.