Pricing, Features, Reviews & Comparison of Alternatives

AI platform for app & website optimization

5.0/5 (1 review) overview

What is, by Scaled Inference, is an artificial intelligence (AI) platform designed to help enterprises enhance metrics through the contextual and continuous optimization of their website, mobile app, UX and UI, using machine learning and monitoring technology. uses AI technology to analyze all available signals and match the user’s variants with precise audience segments. then actively monitors the user’s segments and adapts to any changes to achieve the best metrics over time. operates in two stages; analyze and optimize. First, considers the user’s events and properties in order to learn the key contexts important to the specified key metrics. The solution uses the contextual performance metrics to help design new and improved variations for optimization. can analyze different events including, but not limited to, ‘in the morning at the office working on a Mac’, ‘at the beach on vacation’, ‘running errands on personal time (bad connection)’ or ‘working at night while traveling in Sweden’.’s second stage is optimize. Machine learning technology enables users to see the most relevant variation for each segment.’s optimization tools aim to improve or increase areas such as website customer acquisition rate, media engagement, eCommerce conversion rates despite connection issues, and SaaS app engagement despite travel distractions. To get started, users simply need to get their project key, then observe events and decide actions, before enabling the optimization of actions for metrics. then deploys contextual action policies to the user’s software straight away.


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Value for money
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Business size



United States, Asia, Australia, Brazil, Canada and 8 other markets, China, Europe, Germany, India, Japan, Latin America, Mexico, Middle-East and Africa

Supported languages

English screenshot: optimizes key metrics by matching the most relevant variation to each audience segmentWhy and How to Build Self Optimizing Software with screenshot: focuses on analyzing and optimizing contextual behavior and performance reviews


Very good
Value for money
Ease of use
Customer support
Omer Perchik

Loving SI!

Used daily for less than 6 months
Reviewed 2018-09-07
Review Source: Capterra

Well, that's easy, the fact that it actually works!

It takes time for the data to conclude but this is a general problem of testing.

Rating breakdown

Value for money
Ease of use
Customer support

Likelihood to recommend: 10/10

Minimize review pricing

Pricing options
Free trial
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Contact Scaled Inference for detailed pricing information. features

Activity Dashboard
Assessment Management

Access Control (15 other apps)
Applications Management (13 other apps)
Automatic Notifications (20 other apps)
Collaboration Tools (28 other apps)
Commenting (12 other apps)
Custom Development (21 other apps)
Customizable Branding (15 other apps)
Customizable Templates (16 other apps)
Data Import/Export (16 other apps)
Drag & Drop Interface (23 other apps)
Offline Access (12 other apps)
Permission Management (15 other apps)
Real Time Notifications (13 other apps)
Reporting & Statistics (13 other apps)
Search Functionality (12 other apps)
Third Party Integration (23 other apps)
Workflow Management (18 other apps)

Additional information for

Key features of

  • Funnel analysis
  • Visual editor
  • Test scheduling
  • Multivariate testing
  • Statistical relevance analysis
  • A/B testing
  • User interaction tracking
  • Site search tracking
  • Split testing
  • Landing pages/web forms
  • Website analytics
  • Dashboard
  • Artificial intelligence (AI)
  • Event & property analysis
  • Machine learning
  • Contextual action policies
  • Performance metrics
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Benefits uses Artificial Intelligence to analyze all signals and optimize by matching variants with the precise audience segments.’s continuous optimization use cases include checkout and purchases, subscription, personalization, user experience, cancellations, search engine optimization, and more.

Machine learning technology allows users to see the most relevant variation for each segment, resulting in performance improvement. understands, then deploys contextual action policies to the user’s software straight away. focuses on analyzing and optimizing contextual behavior and performance, rather than traditional analytics and A/B testing.