Startups > Ataccama

Ataccama

Ataccama helps enterprises maintain trusted data through autonomous quality management.
Venture Round $150M total Founded 2007 Toronto, Ontario 390 employees
Ataccama ONE is a unified platform combining data quality, master data management, governance, lineage, and reference data into a single environment purpose-built for trusted agentic AI. The platform autonomously finds and fixes data quality issues across the entire data estate, ensuring data remains trusted, reliable, and AI-ready. Unlike tools that only observe issues, Ataccama manages data quality end-to-end with AI-driven automation. It serves enterprise organizations across banking, financial services, insurance, life sciences, healthcare, and retail that depend on high-quality data for critical business decisions.
Problem solved
Organizations struggle with data that passes schema validation but contains duplicates, stale values, and missing context, leading to poor decision-making and delayed business outcomes.
Target customer
Enterprise organizations (200+ corporate customers) in banking, financial services, insurance, life sciences, healthcare, and retail with complex data estates and high data quality requirements.
Website LinkedIn Crunchbase
Founders
D
David Holes
Founder
Co-founded Ataccama to address data quality issues encountered in data integration projects.
J
Jan Mrazek
Founder
Co-founded Ataccama to address data quality issues encountered in data integration projects.
J
Jan Cervinka
Founder
Co-founded Ataccama to address data quality issues encountered in data integration projects.
P
Petr Jech
Founder
Co-founded Ataccama to address data quality issues encountered in data integration projects.
M
Michal Klaus
Founder & Former CEO
Led Ataccama for 15 years before transitioning to new CEO Mike McKee in recent leadership change.
Funding history
Grant Unknown 2015-01-01 Led by National Science Foundation · Unknown
Series D $150M 2022-06-22 Led by Bain Capital · Unknown
Strategic Investment Unknown 2025-12-09 Led by Snowflake Ventures · Unknown
Total raised: $150M
Industries
Artificial Intelligence Analytics Business Intelligence Cloud Data Services Data Center Automation Data Integration PaaS SaaS Privacy Software
Pricing
Transparent licensing with soft volume limits, no back charges, no penalties for short-term spikes. Averages matter over short-term peaks. Specific pricing not publicly available; contact sales required.
Notable customers
T-Mobile US, Teranet, Heineken, Blue Cross Blue Shield, and approximately 200 corporate customers across banking, financial services, insurance, life sciences, healthcare, and retail, plus 200 additional OEM customers.
Integrations
Snowflake (via Snowflake Ventures partnership), cloud data warehouses, OEM partner ecosystems
Website
ataccama.com/
Competitors
Profisee
Focuses primarily on master data management; Ataccama provides unified platform combining MDM, data quality, governance, and lineage.
Reltio
Customer data platform focused; Ataccama broader platform covering entire data estate management with autonomous remediation.
Collibra Belgium
Data governance-focused; Ataccama combines governance with autonomous data quality and MDM capabilities.
Informatica MDM
Specialized MDM solution; Ataccama integrates MDM with autonomous data quality and end-to-end management capabilities.
Talend
Data integration and ETL platform; Ataccama focuses on data quality, governance, and autonomous remediation rather than integration.
Why this matters: Ataccama raised $150M at a $550M valuation (June 2022) and recently secured strategic investment from Snowflake Ventures, signaling strong market validation in the critical intersection of data quality and enterprise AI. The company's focus on autonomous remediation rather than just observation positions it uniquely as organizations shift from observability to actionable data governance.
Best for: Enterprise organizations managing large, complex data estates that need autonomous data quality management and trust in data-driven decision-making.
Use cases
Financial Services Data Governance
Banks and financial institutions use Ataccama to maintain regulatory compliance and ensure customer data accuracy across systems. Blue Cross Blue Shield reported $30-40M in value from data quality improvements. The platform's autonomous remediation reduces manual data quality work across compliance-critical systems.
Customer 360 Programs
Organizations building unified customer views use Ataccama to consolidate and deduplicate customer records across systems. The platform delivered $1.8M in ROI from customer 360 initiatives with 348% ROI in the first three years, enabling better customer segmentation and personalization.
AI Model Training Data Preparation
Companies preparing data for machine learning models use Ataccama to ensure training datasets are clean, complete, and properly governed. The platform's lineage tracking and autonomous quality management ensures AI models train on trustworthy data, reducing model drift and improving accuracy.
Multi-Source Data Integration
Organizations consolidating data from multiple source systems use Ataccama to manage quality across the integration pipeline. Rather than discovering quality issues after data loads, the platform proactively identifies duplicates, stale values, and missing context to prevent downstream analytics issues.
Alternatives
Profisee Choose Profisee if your primary need is master data management without broader data quality and governance requirements.
Collibra Choose Collibra if governance and cataloging are your primary focus; Ataccama is stronger on autonomous data quality remediation.
Informatica Choose Informatica if you need enterprise data integration alongside MDM; Ataccama is more specialized in quality and governance.
FAQ
What does Ataccama do? +
Ataccama ONE is a unified platform that combines data quality, master data management, governance, lineage, and reference data management. It uses AI-driven automation to continuously find and fix data quality issues across an organization's entire data estate, ensuring data stays trusted, reliable, and ready for AI applications. Unlike tools that only observe problems, Ataccama autonomously remediates data quality issues.
How much does Ataccama cost? +
Ataccama uses transparent, flexible licensing with soft volume limits and no back charges or penalties. Short-term spikes over limits are permitted; long-term exceedances are addressed collaboratively during quarterly reviews. Specific pricing is not publicly available; organizations must contact sales for custom quotes.
What are alternatives to Ataccama? +
Key alternatives include Profisee (specialized MDM), Collibra (governance and cataloging focused), Informatica MDM (enterprise data integration), Reltio (customer data platform), and Talend (data integration and ETL). Ataccama differentiates through autonomous data quality remediation and unified platform combining quality, MDM, and governance.
Who uses Ataccama? +
Ataccama serves approximately 200 corporate customers in banking, financial services, insurance, life sciences, healthcare, and retail. Notable customers include T-Mobile US, Teranet, Heineken, and Blue Cross Blue Shield. The company also has 200 additional OEM customers using the platform through partner integrations. Target buyers are enterprise organizations managing large, complex data estates.
How does Ataccama compare to Informatica? +
Informatica is a comprehensive data integration platform with strong MDM capabilities but requires more manual effort for data quality remediation. Ataccama uniquely combines autonomous data quality management with MDM and governance in a unified platform, offering end-to-end quality management without separate tools. Ataccama is the choice for organizations prioritizing autonomous quality maintenance; Informatica is better for broader data integration pipelines.
What makes Ataccama different from other data quality tools? +
Ataccama is the only platform that manages data quality end-to-end with autonomous AI-driven remediation, not just observation. Rather than alerting teams to problems, the platform automatically fixes duplicates, stale values, and missing context across the data estate. It integrates quality, MDM, governance, and lineage into a single unified environment purpose-built for trusted AI.
Tags
data quality master data management data governance autonomous remediation enterprise AI data lineage observability