The Talent Discovery and Recommendation Platform
That Finds Best Fit Candidates Quickly.
instaTalent’s talent discovery and recommendation platform utilizes web data extraction, text analytics, graph modeling, hierarchical taxonomies, and cognitive behavioral analytics to make employee recruitment more effective and efficient.
- The web data extraction collects data, collates, categorizes and classifies the results into a single coherent information base.
- Text analytics detects natural language patterns in written text, to create some structured information from unstructured and often ambiguous text.
- Graph modeling uses graph theory to analyze interconnections and relationships that may not have been previously discovered.
- Using taxonomies instaTalent is able to determine relationships between words and reflect them in an efficient and direct manner.
- With cognitive behavior analytics, instaTalent analyzes the behaviors as they interact with an environment.
It has been observed that the two most common reasons top talent often gets overlooked during the recruitment process is because of the lack of time and resources necessary to get large stacks of resumes and the poor understanding of the domain for which the recruitment is to be done.
instaTalent addresses these issues in a very unique way. Not being tied to a single source, instaTalent uses web data extraction to ensure that you get the best candidates from multiple rich sources. Text analytics helps bring out the job requirements written in plain English and graph modeling brings out discreet relationships between the job description and resumes.
To understand how domain taxonomies help, consider why a recruiter not familiar with, for example, energy domain, will not be able to do a good job of recruiting energy specialists. The key element lacking here is domain specific knowledge. Taxonomies represent this domain specific knowledge in a way that computers can process and use in decision making. instaTalent uses advanced taxonomies to apply human domain expertise to find the broadest range of candidates possible.
instaTalent goes a step further than any other algorithm-based recommendation platform and analyzes the personality of recommended candidates to evaluate suitability for a specific job. It uses cognitive behavior analytics powered by IBM Watson, to model candidates’ personality profile and matches it with given job requirements.
Once a job description is uploaded, instaTalent immediately extracts all relevant data, analyzes the major job boards, and recommends suitable candidates for that job description in real time. instaTalent is a unique cognitive talent discovery and recommendation platform that shortens your employee hiring cycle without sacrificing quality and accuracy to recommend you the best-fit candidates. Through a highly intuitive graphical interface, it shows various trade-offs involved with candidates and helps you choose the right one.
What is cognitive computing-
Cognitive computing is the simulation of human thought processes in a computerized model.
Cognitive computing involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance.
Cognitive computing systems use machine learning algorithms. Such systems continually acquire knowledge from the data fed into them by mining data for information. The systems refine the way they look for patterns and as well as the way they process data so they become capable of anticipating new problems and modeling possible solutions.
Cognitive computing is used in numerous artificial intelligence (AI) applications, including expert systems, natural language programming, neural networks, robotics and virtual reality. The term cognitive computing is closely associated with IBM's cognitive computer system, Watson.