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Top 1 Data Quality Tools Companies Under $1M Revenue (November 2026)

As of November 2026, Latka tracks 1 data quality tools companies under $1M in annual revenue. They have combined revenues of $660K and employ 6 people.

Every company below sells data quality tools to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.

What Data Quality Tools Companies do

Data Quality Tools are specialized software solutions designed to help organizations assess, improve, and maintain the integrity of their data. These tools enable users to identify data quality issues such as inaccuracies, inconsistencies, or incompleteness, which are crucial for reliable decision-making. Common use cases include data cleansing, validation, monitoring, and profiling, ensuring that organizations operate with accurate and trustworthy data. Typical features of Data Quality Tools encompass data profiling, which analyzes data's structure and content; data cleansing functionalities that standardize and correct data; and deduplication services that eliminate duplicate entries. Buyers of these solutions commonly include IT departments, data management professionals, and data analysts who are responsible for ensuring that accurate data is available across various business functions. As reliance on data increases across industries, the need for robust data quality solutions has become more critical than ever.

Companies
1
Revenue
$660K
Funding
-
Employees
6

Filters

Sorting: Highest -> Lowest

Filters
Revenue
All<$1M$1M-$5M$5M-$10M$10M-$100M$100M+
Funding (Locked)Growth (Locked)Team-Size (Locked)

Top Data Quality Tools Companies Under $1M Revenue

Showing 1 of 1 companies ranked by annual revenue.

1DataGroomr logo
DataGroomr

Philadelphia, Pennsylvania, United States

DataGroomr is the modern, leading-edge solution to Salesforce data quality. Data cleansing is critical for any organization to be successful, but it doesn’t need to be so painful. Duplicate records especially cause all sorts of problems – for sales, marketing, customer support, ops and finance. DataGroomr uses the latest AI techniques to match most accurately, identify the most duplicates, and keep your data clean all the time. No setup or configuration is required; DataGroomr's intelligent duplicate detection algorithms handle everything – and then get even better as they learn your unique data and choices. DataGroomr's easy-to-use apps ensure your Salesforce data is always at its best. And you can trust the DataGroomr team to support you every step of the way. FREE TRIAL ⇨ www.datagroomr.com #salesforce #salesforceadmin #data #datamanagement #crm

Revenue
$660K
Year founded
2018
Team size
6

Frequently asked questions about Data Quality Tools Companies Under $1M Revenue

How many data quality tools companies under $1M in annual revenue are there?

Latka tracks 1 data quality tools companies under $1M in annual revenue. Together they generate $660K in annual revenue and employ 6 people.

Which data quality tools company under $1M in annual revenue is the largest?

DataGroomr is the largest, with $660K in annual revenue, founded in 2018.

How much revenue does a typical data quality tools company under $1M in annual revenue make?

The average data quality tools company in this list makes $660K a year, across 1 companies with reported revenue.

Who are the leading Data Quality tools vendors under $1M in annual revenue?

Ranked by annual revenue, the leaders are DataGroomr.

Related IT Infrastructure Software categories

All IT Infrastructure Software SaaS categoriesEvery category we track inside IT Infrastructure Software, each ranked by revenue.Browse every SaaS industryThe full A-Z of SaaS categories Latka tracks, from Data Quality to everything else.

Inclusion Criteria

- These tools must provide data profiling capabilities to analyze data quality. - They should include data cleansing features to correct inaccuracies and inconsistencies. - Deduplication functions are essential to remove duplicate entries from datasets. - Data Quality Tools must support ongoing monitoring of data quality over time. - They should facilitate data validation against established standards or rules. - Not just data storage solutions; must also offer active data quality improvement functionalities.