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Top Espafil Alternatives, Competitors & Similar Software

Founded 2011

Find 20 competitors in the Data Science and Machine Learning Platforms. Compare other SaaS such as Synaps Labs, Semantic Software and Semantic Software. These Espafil competitors have raised $26.2M and together serve more than 11K customers and employ over 101 team members.

Compare Espafil with Synaps Labs
1
Synaps Labs

Data Science and Machine Learning Platforms

Synaps Labs is a SaaS platform for digital out-of-home (OOH) advertising aimed at: - Bringing digital advertising capabilities to OOH - Enabling dynamic yield management based on real-time audience - Creating cross-channel attribution between OOH & Digital

Revenue
$645.5K
Customers
-
Year founded
2016
Funding
-
Team size
2
Location
United States
Compare Espafil with Semantic Software
2
Semantic Software

Data Science and Machine Learning Platforms

Build your own Artificial Intelligence Systems and teams. The Cognitive Software Group is a bespoke AI Technology and Consultancy company with extensive IP and patents. Using our cognitiveAI platform, Enterprises can become largely self-sufficient in building AI systems within a year, led by a small team of customer Super Users that become experts in extracting knowledge from various sources of data. Our Cloud-based product offering, cognitiveAI, uses Machine Learning Neural Networks to extract knowledge from electronic documents (including scans of text) and from computer databases to create a computer knowledge system known as a 'semantic graph' that is essential for Artificial Intelligence.

Revenue
$646.5K
Customers
-
Year founded
2008
Funding
-
Team size
3
Location
Australia
Compare Espafil with Semantic Software
3
Semantic Software

Data Science and Machine Learning Platforms

Build your own Artificial Intelligence Systems and teams. The Cognitive Software Group is a bespoke AI Technology and Consultancy company with extensive IP and patents. Using our cognitiveAI platform, Enterprises can become largely self-sufficient in building AI systems within a year, led by a small team of customer Super Users that become experts in extracting knowledge from various sources of data. Our Cloud-based product offering, cognitiveAI, uses Machine Learning Neural Networks to extract knowledge from electronic documents (including scans of text) and from computer databases to create a computer knowledge system known as a 'semantic graph' that is essential for Artificial Intelligence.

Revenue
$646.5K
Customers
-
Year founded
2008
Funding
-
Team size
3
Location
Australia
Compare Espafil with Puying Intelligence
4
Puying Intelligence

Data Science and Machine Learning Platforms

Developer of a AI-empowered insurance claims processing engine. The company's technology helps clients reduce fraudulent claims and processing time, enabling insurance companies to more efficiently process claims.

Revenue
$645.1K
Customers
-
Year founded
2017
Funding
-
Team size
13
Location
China
Compare Espafil with Puying Intelligence
5
Puying Intelligence

Data Science and Machine Learning Platforms

Developer of a AI-empowered insurance claims processing engine. The company's technology helps clients reduce fraudulent claims and processing time, enabling insurance companies to more efficiently process claims.

Revenue
$645.1K
Customers
-
Year founded
2017
Funding
-
Team size
13
Location
China
Compare Espafil with Swiftype
6
Swiftype

Data Science and Machine Learning Platforms

Swiftype is a cloud-based search platform that provides all the tools you need to create fantastic search experiences.

Revenue
$644.2K
Customers
1K
Year founded
2012
Funding
$22.2M
Team size
4
Location
United States
Compare Espafil with Exoshock
7
Exoshock

Data Science and Machine Learning Platforms

Provider of an online risk management platform designed to enable organizations to understand the global economic changes that will impact them. The company's platform offers a transitional global risk model that captures general trends in economic activity by incorporating global and regional markets and calibrated against historical data by integrating hybrid econometric model to address dynamics and inertia within world regions, and uses the power of financial and trade networks to model the numerous interactions, enabling organizations to get access to global statistical data, relevant models, analysis and a range of possible outcomes for relevant scenarios for a better planning of managing risks.

Revenue
$644.2K
Customers
-
Year founded
2015
Funding
-
Team size
3
Location
United Kingdom
Compare Espafil with cClearly, Inc.
8
cClearly, Inc.

Data Science and Machine Learning Platforms

Provider of marketing analytics and optimization technology intended to uncover new customer insights and improve paid search performance. The company's software uses machine learning algorithms and a proprietary database of millions of external facts and events to automatically find and act on insights in the marketer's data, helping marketers increase revenues and lower their customer acquisition costs.

Revenue
$644.2K
Customers
-
Year founded
2014
Funding
-
Team size
3
Location
United States
Compare Espafil with PredictWise
9
PredictWise

Data Science and Machine Learning Platforms

Developer of data analysis platform intended to reflect on academic, polling, prediction markets and social media. The company offers cost-effective, fast and flexible polling with an emphasis on politics and finance by entering polling data with machine-learning based post-polling analytics, enabling users to generate money markets and trade in contracts of upcoming events.

Revenue
$644.2K
Customers
-
Year founded
2017
Funding
$250K
Team size
3
Location
United States
Compare Espafil with cClearly, Inc.
10
cClearly, Inc.

Data Science and Machine Learning Platforms

Provider of marketing analytics and optimization technology intended to uncover new customer insights and improve paid search performance. The company's software uses machine learning algorithms and a proprietary database of millions of external facts and events to automatically find and act on insights in the marketer's data, helping marketers increase revenues and lower their customer acquisition costs.

Revenue
$644.2K
Customers
-
Year founded
2014
Funding
-
Team size
3
Location
United States
Compare Espafil with PredictWise
11
PredictWise

Data Science and Machine Learning Platforms

Developer of data analysis platform intended to reflect on academic, polling, prediction markets and social media. The company offers cost-effective, fast and flexible polling with an emphasis on politics and finance by entering polling data with machine-learning based post-polling analytics, enabling users to generate money markets and trade in contracts of upcoming events.

Revenue
$644.2K
Customers
-
Year founded
2017
Funding
$250K
Team size
3
Location
United States
Compare Espafil with Datacrushers
12
Datacrushers

Data Science and Machine Learning Platforms

Datacrushers is a revenue discovery platform and global leader in site-wide revenue and cart recovery and acceleration. Founded in 2015, Datacrushers uses Machine Learning and A.I. along with NLP to identify and recover revenue loss, cart abandonment and new revenue sources across any site. We complete the deep ongoing analysis of eCommerce websites by monitoring the three main focal points of any site. The User, Site and Product. Unlike traditional cart abandonment platforms, Datacrushers does not require shoppers and customers to be logged-in to conduct both on and offsite campaigns. We use a wide range of data-driven and analytics based conversion tools to target the shopper at the right time with the most accurate and effective campaign to drive the sale. Our service is completely platform, language and currency agnostic and only require 1.5 lines of JS. Meaning an ultra-fast, go-to-market with minimal set-up time and tech intervention. Datacrushers is based out of Jerusal

Revenue
$644.2K
Customers
-
Year founded
2014
Funding
-
Team size
4
Location
Israel
Compare Espafil with PredictWise
13
PredictWise

Data Science and Machine Learning Platforms

Developer of data analysis platform intended to reflect on academic, polling, prediction markets and social media. The company offers cost-effective, fast and flexible polling with an emphasis on politics and finance by entering polling data with machine-learning based post-polling analytics, enabling users to generate money markets and trade in contracts of upcoming events.

Revenue
$644.2K
Customers
-
Year founded
2017
Funding
$250K
Team size
3
Location
United States
Compare Espafil with cClearly, Inc.
14
cClearly, Inc.

Data Science and Machine Learning Platforms

Provider of marketing analytics and optimization technology intended to uncover new customer insights and improve paid search performance. The company's software uses machine learning algorithms and a proprietary database of millions of external facts and events to automatically find and act on insights in the marketer's data, helping marketers increase revenues and lower their customer acquisition costs.

Revenue
$644.2K
Customers
-
Year founded
2014
Funding
-
Team size
3
Location
United States
Compare Espafil with CN2
15
CN2

Data Science and Machine Learning Platforms

Provider of an online content management platform intended to automate and circulate business content. The company's platform offers easy and centralized location to manage all of artificial intelligence application assets, 2D, 3D and AR assets which may be stored and permissions assigned to ensure the content is accessible and available whenever needed, enabling content developers to quickly and easily create compelling artificial intelligence applications for sales, marketing, service and training applications.

Revenue
$644.2K
Customers
-
Year founded
2011
Funding
-
Team size
3
Location
United States
Compare Espafil with CloudTags
16
CloudTags

Data Science and Machine Learning Platforms

CloudTags created a flexible data-driven pop-up ecosystem that engages customers on their smartphones.

Revenue
$644.2K
Customers
-
Year founded
2012
Funding
$2M
Team size
4
Location
United States
Compare Espafil with Woohoo
17
Woohoo

Data Science and Machine Learning Platforms

Developer of an e-commerce engagement technology designed to bring gamification intelligence to increase engagement delivering personalization and custom audience creation. The company's technology uses gamification, machine learning, and artificial intelligence to increase user engagement by adding gamification to pop-ups, enabling companies to increase subscribers and boost sales.

Revenue
$644.2K
Customers
5K
Year founded
2017
Funding
-
Team size
3
Location
Israel
Compare Espafil with Woohoo
18
Woohoo

Data Science and Machine Learning Platforms

Developer of an e-commerce engagement technology designed to bring gamification intelligence to increase engagement delivering personalization and custom audience creation. The company's technology uses gamification, machine learning, and artificial intelligence to increase user engagement by adding gamification to pop-ups, enabling companies to increase subscribers and boost sales.

Revenue
$644.2K
Customers
5K
Year founded
2017
Funding
-
Team size
3
Location
Israel
Compare Espafil with Aivy
19
Aivy

Data Science and Machine Learning Platforms

Scientific Diagnostic-SaaS that helps HR to achieve a 5x better pre-selection and avoid 30 % of their bad hires before the first interview.

Revenue
$644.2K
Customers
-
Year founded
2016
Funding
$1.2M
Team size
20
Location
Germany
Compare Espafil with Alchemai
20
Alchemai

Data Science and Machine Learning Platforms

SAAS, Supply Chain Network Risk Technology, AI, ML, Data Science

Revenue
$649.5K
Customers
-
Year founded
2017
Funding
-
Team size
5
Location
United States
Top Espafil Alternatives, Competitors & Similar Software | GetLatka