Data Science Strategy


Intelligent Agent

John McCarthy a thought leader in Cognitive Computer Sciences, coined the term “Intelligent Agent (IA)” in 1955 as "the science and engineering of making intelligent machines." Artificial intelligence (AI) focuses on the design of intelligent agents and the development of intelligence in machines. An Intelligent Agent is a system that perceives its environment and takes actions to maximize its chances of success.  


Design and Development

Artificial intelligence and Machine Learning development is divided into several sub-categories to address specific technical issues and venues. AI application development challenges focus around the emulation of human traits such as reasoning, knowledge, planning, learning, communication, perception.  AdvancedTSC’s platform development capabilities span several approaches to include statistical methods, computational intelligence, and versions of search and mathematical optimization, logic, probability, and economics.


Expert System

Expert System is an interactive computer-based decision-making tool that uses both facts and heuristics to solve difficult decision-making problems based on acquired knowledge. An expert system compared with traditional computer:

· Inference engine + Knowledge = expert system (Algorithm + data structures = program in traditional computer)


Data Science Strategy

Development teams consist primarily of data scientists and DevOps experts. An initial step is to build an API – connector to grab and process data. A considerable amount of effort is dedicated to cleaning up existing data, as the overall platform success hinges upon data cleansing, munging and enrichment considering the potential for growth of external data sources, current data processing module must have a highly scalable architecture for rapid growth or expansion with existing and added sources onboard.  Fully understanding the data is extremely important in driving development success, thus the data is run against a set of data modeling tools to establish descriptive statistics and comprehension of the given data. 

The PCA (Principal Component Analysis) is conducted to understand weights and how key features affect outcome. 

The 10 Rule - with PCA accomplished a model testing plan is devised starting with 10 "competitors" the list is distilled down to the four key models and amalgamated into an ensemble. Note: In predictive analytics and machine learning, ensemble methods incorporate multiple learning algorithms to obtain better predictive performance than can be obtained through constituent learning algorithms alone. 

AI Vehicle Telematics


Vehicle Telematics

Vehicle Telematics has evolved exponentially from a rudimentary diagnostic reporting platform into a highly complex Omni-channel communications solution. Legacy Telematics platforms consisted of electro-mechanical / electro-magnetic sensory devices working in conjunction with on-board computer operating systems to aggregate data points and report on repeatable, predisposed functions through transceiver links to radio or satellite mediums.


Clarity's AI Decision Engine

Acquired Insights has invested a significant amount of technology capital into the development of their AI platform, Clarity.
Clarity  is comprised of a highly sophisticated "Decision Engine" encompassing  complex mathematical algorithms enabling light-speed predictive data  analytics spanning multiple technologies including Telematics. Clarity's  AI Decision Engine can process tremendous volumes of unstructured data  (like video), automating once laborious manual processes, improving time  to resolution and eliminating false positives.

AI Talent Acquisition Optimization


AITAPS - Artificial Intelligence Talent Acquisition

ATSC working closely with Acquired Insights have taken the guess work out of Sourcing & Recruitment utilizing Artificial Intelligence and Machine Learning Predictive Analytics to optimize Talent Acquisition & Employee Workforce Performance 



Phase I - Applicant Assessment

Clarity Role-Fit-Survey - Acquired Insights, customized data gathering Role-Fit-Survey is embedded into each on-line application for candidate input. Applicant queries are designed to meet cultural and role expectations for each position sought within the organization providing distinguishable characteristics for each applicant


Phase II - Real-Time Predictive Analytics

Clarity is a stand-alone solution, however, ATSC works closely with Acquired Insights to integrate Clarity's Real-Time AI & ML capabilities with existing applicant tracking system (ATS)  (i.e. iCIMS, Zoho, Workday, etc.)  to deliver a robust, cost saving Talent Acquisition solution.


Phase III - Workforce Assessment

Acquired Insights Role-Fit-Survey is an ideal Performance and  Workforce Optimization solution. Real-Time Predictive Data Analytics:

  • Support Career Path and Progress decisions by aligning employees with suitable and eligible roles and responsibilities within the organization
  • Support early Leadership recognition, Strategic Succession Planning & Management to eliminate unnecessary external talent acquisition efforts 


Acquired Insights' Clarity Solution

A secure Artificial Intelligence Closed Loop Predictive Analytics platform that scans and processes information in structured and unstructured data repositories using all digital formats.

Through Big Data Analytics, AI, ML, and Deep Learning valuable insights are attained to help automate and improve process, mitigate risk, increase competitiveness and reduce operational cost. For more information go to: