What digna does

digna GmbH is a Vienna-based software company that builds an AI-driven data quality and observability platform deployed entirely on-premises or in private cloud environments within the customer's own database infrastructure. The platform is modular, comprising five specialized modules — Data Anomalies (adaptive AI-driven anomaly detection), Data Analytics (time-series analysis with regression, smoothing, and quantile methods), Data Timeliness (AI-pattern-based arrival monitoring), Data Validation (record-level rule-based checks with multi-column uniqueness and referential integrity), and Schema Tracker (DDL change detection). All checks execute directly inside the customer's database engine, so data never leaves the environment, and an optional Python SDK extends programmatic access for developers and data scientists.

The platform is offered via annual enterprise subscriptions with quote-based pricing and a direct field-sales motion targeting enterprise data teams in regulated industries — finance (primary), healthcare, telecommunications, and public sector. digna's competitive positioning emphasizes European data sovereignty, in-database execution without SaaS, AI that replaces manual rule maintenance, and deployment in under two hours. The company has integrated with 18+ data platforms across warehouses, data lakes, and ETL/orchestration tools, including Snowflake, Databricks, BigQuery, Redshift, Oracle, PostgreSQL, Spark, Airflow, dbt, Informatica, and Talend.

digna is privately held (digna GmbH, Austria) and led by co-founder and CEO Marcin Chudeusz alongside CTO Johann Haller and co-founder/chief scientific officer Danijel Kivaranovic. The company has disclosed only modest non-dilutive grant funding (~$255K across two rounds from Vienna Business Agency and austria Wirtschaftsservice in 2020-2021), employs 11-50 people, and has released six major platform versions between December 2024 and June 2026. Only one named customer (ITS.V) is publicly disclosed, and no revenue figures have been reported.

Name

digna

Legal name

digna GmbH

Website

https://digna.ai

Company type

Private

Founded year

2020

Operating status

Operating

Headcount range

1–10 employees

Short description

digna is a Vienna-based software company that provides an AI-driven, on-premises data quality and observability platform for enterprise data teams in regulated industries, executing checks inside the customer's own database across finance, healthcare, telecom, and public sector.

Ownership category

akta.pro rank

Product category

Data Quality & Observability Software

NAICS

Software Publishers (5132), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518)

SIC

Services-Prepackaged Software (7372), Services-Computer Processing & Data Preparation (7374)

akta.pro primary industry

Monitoring, Observability & Incident Response (alerts, traces, runtime monitoring) (FSAPABAJ)

akta.pro secondary industry

IT Asset Discovery, Inventory & CMDB Services (BPAEAOAE)

Keywords

• Data quality platform
• Data observability software
• AI anomaly detection
• Data validation tools
• Schema change monitoring

Headquarters

HQ city

Vienna

HQ country

Austria

HQ region

Europe

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Marketing or Sales, Operations

Revenue model

1. Platform Subscription/License: digna operates on an enterprise software licensing model with annual or multi-year subscriptions for its data quality and observability platform. Given the on-premises/private cloud deployment model and enterprise focus, pricing is likely quote-based with volume considerations for database connections and data volume.

Pricing tiers

Go-to-market motion1 record

Distribution channels1 record

Marketing channels6 records

Core offering

digna sells an AI-driven data quality and observability platform that executes entirely inside the customer's database environment (on-premises or private cloud). The platform uses adaptive statistical monitoring and machine learning to automatically detect anomalies, validate records, monitor data timeliness, and track schema changes without requiring manual rule configuration. It is delivered as a modular enterprise software license across five specialized modules with an optional Python SDK for programmatic access.

Product overview

digna is a modular AI-driven data quality and observability platform deployed on-premises or in private cloud environments. The platform consists of five core modules: Data Anomalies (AI-based anomaly detection), Data Analytics (time-series analysis), Timeliness (data arrival monitoring), Data Validation (rule-based record-level checks), and Schema Tracker (DDL change detection). All modules execute data quality checks directly within the customer's database, ensuring data never leaves the environment. An optional Python SDK extends programmatic access to platform capabilities for integration into modern data workflows.

Differentiator

Problem solved

Functional benefit

Products and services

• digna Data Anomalies AI-powered anomaly detection module that automatically learns normal data behavior and continuously monitors for unexpected changes in data volumes, distributions, and missing values without manual rule configuration. Targeted at enterprise data teams in regulated industries.
• digna Data Analytics Time-series analytics module that analyzes historical observability metrics to uncover trends, volatility, and statistical patterns, including interactive charting with regression analysis, smoothing techniques, and quantile analysis.
• digna Timeliness Data arrival monitoring module that combines AI-learned patterns with user-defined schedules to detect delays, missing loads, or early deliveries in enterprise data pipelines.
• digna Data Validation Rule-based data validation module supporting record-level checks for business logic enforcement, audit compliance, and targeted data quality control, including multi-column uniqueness checks, referential integrity validation, reusable enumerations, and validation rule templates.
• digna Schema Tracker Schema monitoring module that continuously monitors structural changes in configured tables, identifying added or removed columns and data type changes to detect DDL modifications.
• digna Python SDK Python software development kit enabling programmatic access to digna platform capabilities, allowing developers to create projects, configure datasets and tables, start inspections, retrieve results, and integrate workflows into existing systems. Distributed via PyPI.

Quantifiable outcome

• A large enterprise data warehouse operated for 12 months using AI-driven anomaly detection instead of traditional manual data quality rules, replacing thousands of manual validation controls
• +1 more outcomes

Named customers1 record

Segments4 records

Ideal customer profiles1 record

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration18 records

AI capability4 records

Feature13 records

Partnerships

Ten partnerships are on record, tiered core.

• TeradatacoreTechnology or IntegrationIntegration partnership enabling connection to Teradata databases for data quality monitoring and anomaly detection.
• SnowflakecoreTechnology or IntegrationIntegration partnership enabling connection to Snowflake data warehouse for data quality monitoring.
• Google BigQuerycoreTechnology or IntegrationIntegration partnership enabling connection to BigQuery for data quality monitoring.
• Amazon RedshiftcoreTechnology or IntegrationIntegration partnership enabling connection to Amazon Redshift data warehouse.
• Oracle DatabasecoreTechnology or IntegrationIntegration partnership enabling connection to Oracle databases.
• PostgreSQLcoreTechnology or IntegrationIntegration partnership enabling connection to PostgreSQL databases.
• Microsoft SQL ServercoreTechnology or IntegrationIntegration partnership enabling connection to MS SQL Server databases.
• MySQLcoreTechnology or IntegrationIntegration partnership enabling connection to MySQL databases.
• HadoopcoreTechnology or IntegrationIntegration with Hadoop data lakes for data quality monitoring.
• DatabrickscoreTechnology or IntegrationIntegration with Databricks for data quality monitoring in lakehouse environments.

Scale indicators1 record

Recent moves5 records

Expansion highlights5 records

Broad incumbents

• Talend (Qlik): Enterprise data integration and data quality vendor (now part of Qlik), offering data profiling, cleansing, and validation across hybrid environments. Competes with digna for ETL-adjacent data quality workloads.
• Informatica: Enterprise data integration and quality incumbent offering Data Quality, Master Data Management, and observability within a broad platform. Competes with digna in large enterprise data quality deals, especially with Informatica integration partnerships.
• Collibra: Data intelligence and governance platform offering data catalog, lineage, and quality capabilities for large enterprises. Adjacent incumbent with overlapping enterprise buyers in regulated verticals.
• IBM Databand: IBM's data observability offering (originally Databand) for pipeline monitoring, anomaly detection, and data quality within broader IBM data fabric stacks. Broad incumbent competing in the same enterprise data quality category.

Direct peers

• Bigeye: Data observability platform offering automated data quality monitoring, anomaly detection, and metric analysis across cloud data warehouses. Competes head-to-head with digna's Anomalies and Validation modules.
• Great Expectations (Snowflake): Open-source data validation framework (now part of Snowflake) used for data quality testing in pipelines. Overlaps directly with digna's Data Validation module and benefits from Snowflake distribution.
• Datafold: Data observability and data diffing platform focused on anomaly detection, schema change tracking, and pipeline monitoring. Direct overlap with digna's Anomalies and Schema Tracker modules.
• Ataccama: AI-powered data quality and governance platform with strong European roots, serving regulated industries with both cloud and on-premises deployment options. Closest direct European peer to digna with similar vertical focus.
• Monte Carlo: A leading data observability platform providing automated data quality monitoring, anomaly detection, and lineage. Closest direct competitor to digna, though delivered as cloud SaaS rather than in-database/on-prem.
• Soda: Data quality and observability vendor with an open-source core (Soda Core) and SaaS offering, focused on data testing, anomaly detection, and freshness monitoring. Direct overlap with digna's validation and timeliness modules.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks7 records

Key highlights7 records

Customer concentration

Revenue estimate

Valuation estimate

Number of profiles

Profiles3 records

Funding overview

Funding rounds2 records

Investors2 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about digna