This document discusses building a machine assisted, auto-governed platform for enablement leaders and admins to effectively run sales enablement programs. The platform would provide a personalized, contextual experience based on best practices, company culture, user priorities, and activities. It would also integrate external metrics for a 360-degree view and significantly reduce the time admins spend running enablement initiatives. The document outlines designing a data pipeline to extract meaningful text from platform data and using natural language generation templates. It also covers concepts for personalizing and contextualizing the system based on criticality, as well as including visualization tools.

1. A journey of AI driven
analytics insights engine
By Somya Anad

2. Abstract
At Mindtickle, we deal with different persona interaction like managers, learners, admins and site
owners. Given the complexity of the platform, it is difficult to keep track of the most critical activites
admist of all ongoing activities. We want to build a machine assisted auto governed platform for leaders
& admins to effectively run best enablement programs for their sales te

3. Vision
● A machine assisted auto governed platform for enablement leaders & admins to effectively run
best enablement programs for their sales teams
● Personalized & Contextual based on best practices, company culture & priority and user’s
activities
● Significant Reduction in time for admins to run enablement initiatives
● 360 degree view enabled by pulling in external metrics through integration

4. Why is this relevant?
● Scope of the current AI scenario in tech space.
● How it can solve a general use-case?

5. Making sense out of data
● Understanding the subjective nature of data
● Data cleaning and its further scope.
● Data modelling of various kinds of data.
● Feature engineering
● Finding anomalies in the data.

6. Data to text pipeline architecture
1. Designing a pipeline which will empower the entire mechanism of getting data out of your
platform into meaningful text.
2. Why a natural language generation templating system should be used?

7. Personalization and criticality
Concepts to drive personalization and contextualisation in your system

8. Visualisation tools

9. Questions?

10. Thank you!