Our Science of Aligning Human Technical Capacity to Ideas

Solving an evolving challenge

Framework Science, a U.S. Software company with operations across Latin America, created an AI-driven IT Workforce Automation platform called TeamStation AI for many reasons.

First, the company wanted to develop a more efficient and effective way to hire and manage talent.

Second, the company wanted to help organizations overcome the challenges of finding and hiring top talent in a competitive market.

Third, the company wanted to redefine human capacity by enabling organizations to tap into the full potential of their employees.

TeamStation AI is a powerful tool that can help organizations to:

• Improve their hiring process
• Reduce the risk of bad hires
• Increase the chances of finding top talent
• Boost employee productivity and engagement
• Improve organizational performance

Scope and mapping Decision making

Technical skills

TeamStation AI uses various methods to assess a candidate's technical skills, including: Platform mentioned in the news .

• Resume review: TeamStation AI uses natural language processing (NLP) to extract relevant information from candidates' resumes, such as their programming skills, experience with specific technologies, and relevant certifications.
• Online coding challenges: TeamStation AI uses online coding challenges to assess a candidate's skills in specific programming languages and frameworks.
• Technical interview: TeamStation AI also conducts technical interviews with candidates to assess their technical knowledge and skills in more depth.

Behavioral traits

TeamStation AI uses a variety of methods to assess a candidate's behavioral traits, including:

• Interview performance: TeamStation AI uses NLP to analyze a candidate's interview performance and identify keywords and phrases that are associated with specific behavioral traits, such as communication skills, problem-solving skills, and teamwork skills.
• Online reviews: TeamStation AI also collects online reviews of candidates from previous employers and colleagues. These reviews can provide valuable insights into a candidate's behavioral traits.
• Social media activity: TeamStation AI also analyzes a candidate's social media activity to identify patterns and behaviors associated with specific behavioral traits.

Personality traits

TeamStation AI uses a variety of methods to assess a candidate's personality traits, including:

• Interview performance: TeamStation AI uses NLP to analyze a candidate's interview performance and identify keywords and phrases associated with specific personality traits, such as extraversion, agreeableness, and conscientiousness.
• Personality tests: TeamStation AI also offers personality tests to candidates. These tests can provide valuable insights into a candidate's personality traits.
• Social media activity: TeamStation AI also analyzes a candidate's social media activity to identify patterns and behaviors associated with specific personality traits.

Defining Capacity

Once TeamStation AI has collected all this data, it uses various machine learning algorithms to identify patterns and trends. These patterns and trends can predict a candidate's ability to perform a job successfully.

For example, TeamStation AI might identify a pattern that suggests that candidates with a particular combination of programming skills, experience, and personality traits are more likely to be successful in a particular role. The platform can then use this information to match our Nearshore Talent with our client's jobs, and they are most likely to succeed.