Automated Report Generation with Supertype Summary, a done-for-you programmatic PDF generation service.
Supertype Summary creates a highly tailored pipeline that output bespoke PDF in seconds, not days or hours.
Because your time is too valuable to be looking for insights from millions of data points across multiple services, Summary consolidates your most important data feeds and puts them all in a digestible, insightful, actionable format — delivered to your inbox on a schedule that works for you.
Programmatic Report Generation, in seconds.
Supertype Summary connects with your first-party data feeds (in-house database, API etc) or third party data sources (AppStore, e-Commerce analytics, payment service, API subscriptions etc).
It analyzes the data, and organize them into actionable sections of information spread across beautifully crafted PDF pages. To achieve this task Supertype Summary uses state-of-art NLP and custom-train AI models so all reports are truly one of a kind, especially crafted to maximize business value for you.
How Does it Work?
Not just any automated report. Supertype Summary is built with state-of-the-art NLP / language models and an automatic, proprietary insights discovery process. Our data scientists and engineers work with you to define the data feeds for your PDF report generation pipeline, and develop the automation alongside your feedback.
1 Data Feeds
2 PDF Components
3 Delivery & Automation
Bespoke Solution without compromise
From guided on-boarding, followed by tailor-made solution delivery, to a fully personalized consuting experience.
Schedule a Demo
Schedule a call with us to see Supertype Summary in action and explore how our done-for-you programmatic reporting service could save you lots in manpower.
Read about our processes
Working with app review analytics: the data science methodologies, tools and problem-solving frameworks you need to make sense of customer reviews
Multiple approaches to dimensionality reduction for pattern discovery, visualization and drawing decision boundaries (PCA, FAMD, PCAmix)
A journal entry on topic extraction from text (app reviews, e-commerce text reviews), using supervised, unsupervised and semi-supervised approaches