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Top 6,950 Other Analytics Software SaaS Companies in May 2026

As of May 2026, there are 6,950 SaaS companies in Other Analytics Software. They have combined revenues of $73.1B and employ 478.3K people. They have raised $72.6B and serve 6.6B customers combined.

Other Analytics Software encompasses a wide range of tools designed to analyze various types of data not covered by more mainstream analytics platforms. These tools often cater to specific niches or unique data types, enabling organizations to gain insights that may not be available through traditional analytics solutions. Use cases include performance tracking, advanced data modeling, and specialized market analysis, which are essential for data-driven decision-making across diverse sectors. Common features of Other Analytics Software may include custom reporting capabilities, unique data visualization tools, and integration with a variety of data sources. Workflows often involve data importing, processing, analysis, and visualization, allowing users to transform raw data into actionable insights tailored to their specific needs. Typical buyer personas include data analysts, marketing teams, and operations managers who seek specialized insights to inform strategic decisions.

Companies
6,950
Revenue
$73.1B
Funding
$72.6B
Employees
478.3K

Filters

Sorting: Highest -> Lowest

Filters

Top Other Analytics Software Companies

Showing 10 of 2,581 companies ranked by annual revenue.

1
Gaiascope

Boston, Massachusetts, United States

SaaS that helps renewables & energy storage operate more profitably

Revenue
$5M
Customers
-
Year founded
2019
Funding
-
Team size
10
Growth
-
2
NuMind

Cambridge, Massachusetts, United States

Create custom NLP models

Revenue
$5M
Customers
-
Year founded
2022
Funding
-
Team size
10
Growth
-
3
Mona

Atlanta, Georgia, United States

Mona is a SaaS monitoring platform for Data and AI driven systems

Revenue
$5M
Customers
-
Year founded
2018
Funding
$3.9M
Team size
6
Growth
-
4
Response Labs

Baltimore, Maryland, United States

Omnichannel customer relationship management marketing agency helping companies manage data for personalized messaging at scale across channels and formats

Revenue
$5M
Customers
-
Year founded
2014
Funding
-
Team size
22
Growth
-
5
Arroyo

Berkeley, California, United States

Cloud-native stream processing

Revenue
$5M
Customers
-
Year founded
2022
Funding
-
Team size
2
Growth
-
6
Klardata

San Francisco, California, United States

Business intelligence & analytics for startups

Revenue
$5M
Customers
-
Year founded
2016
Funding
-
Team size
1
Growth
-
7
Lakarya

Sterling, Virginia, United States

Delivers custom data analytics, cloud, security and mobile products and services that help global enterprises across industries achieve business results. Also specializes in IT Network Infrastructure and Data Center Management

Revenue
$5M
Customers
-
Year founded
2015
Funding
-
Team size
30
Growth
-
8
Paradigma Software

Beaverton, Oregon, United States

SQL Admin | Reporting | DB Diagramming | Forms & more, Database | Reporting | Forms Server

Revenue
$5M
Customers
-
Year founded
1998
Funding
-
Team size
6
Growth
58.08%
9
Powder

, United States

AI Agents for precise document analysis

Revenue
$5M
Customers
-
Year founded
2023
Funding
-
Team size
25
Growth
-
10
FI Navigator Corporation

Atlanta, Georgia, United States

Data and analytics platform company serving vendors, advisors and financial institutions of the U.S. banking sector to optimize revenue generation

Revenue
$5M
Customers
-
Year founded
2014
Funding
-
Team size
7
Growth
-

Inclusion Criteria

- The software must facilitate advanced data analysis functionalities. - It should provide unique reporting and visualization capabilities that are not typically found in mainstream analytics tools. - The product must support integration with a variety of data sources, including specialized databases. - It should cater to specific industries or use cases that require niche analytical features. - Not just data visualization; it must also include tools for data processing and modeling. - The software should be user-friendly for non-technical users while still offering advanced features for data experts.