Trillium provided comprehensive data quality and governance solutions that enabled enterprises to cleanse, standardize, match, and enrich their critical business data across multiple systems and databases.
Last updated Mar 8, 2026 by AI Enrichment
- Industry
- Data Quality & Management
- Business Model
- SaaS
- Target Market
- Enterprise
- Employee Count
- 51-200
- Funding
- acquired
- Revenue Range
- $10M-$50M
- Stock Symbol
- NASDAQ:TRIL
- Parent Company
- Precisely
- API Available
- Yes
Market Position
Trillium was recognized as a leader in enterprise data quality solutions before its acquisition
Overview
Trillium Software was a leading provider of data quality, data profiling, and data governance solutions that helped organizations improve the accuracy, consistency, and reliability of their enterprise data. Founded in 1992, the company specialized in data cleansing, matching, and enrichment capabilities that enabled businesses to maintain high-quality customer and operational data across multiple systems and databases. Trillium's solutions were particularly valued for their ability to handle complex data quality challenges in large-scale enterprise environments. The company was acquired by Syncsort in 2010, which integrated Trillium's data quality capabilities into its broader data management portfolio. Syncsort itself was later rebranded as Precisely in 2020 following its merger with Pitney Bowes Software & Data. Today, Trillium's technology lives on as part of Precisely's data integrity suite, continuing to serve enterprise customers who require robust data quality and governance solutions. While the Trillium brand is no longer actively marketed as a standalone entity, its core technology and methodologies remain embedded in Precisely's product offerings.
Products & Features
Trillium Software System
Core data quality platform for data profiling, cleansing, matching, and enrichment
Data Profiling
Automated analysis and assessment of data quality issues
Data Cleansing
Standardization and correction of data inconsistencies
Data Matching
Identification and linking of duplicate records across systems
Key Features
Advanced data matching and deduplication algorithmsMulti-domain data quality (customer, product, vendor data)Data profiling and quality assessmentAddress standardization and verificationGlobal name and address parsingData enrichment capabilities
Use Cases
Customer data integration and master data managementData migration and consolidation projectsCRM data quality improvementRegulatory compliance and data governanceMarketing database optimization
Customer Segments
Large enterprisesFinancial services institutionsHealthcare organizationsRetail and consumer goods companiesTelecommunications providers