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Introducing Sidekick a.i.

The Future Of Application Management Is Here.

Meet “Sidekick”, the industries first AI Assistant for Application Management. Sidekick powers recognition awards, scholarships, grants, fellowships, and abstracts by incorporating intelligent automation and A.I./Plagiarism detection to streamline processes, improve decision-making, and elevate the applicants experience.

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5 ways AI will transform application management

Discover how AI will impact award, grant, scholarships, fellowship, abstracts, and more to streamline processes, ensure fairness, and optimize resources. Learn how automated systems match applicants to opportunities, create efficiencies, and check for AI generated application content.

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Intelligent Automation

Sidekick leverages intelligent automation to create a personalized experience for participants, ensuring quality data collection, opportunity visibility, and consolidated workflows.

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The AI Assistant for Grant Management dashboard visualizes how sidekick AI will innovate grantmaking.
 
Intelligent Program Matching in Sidekick utilizes a sophisticated algorithm to create a detailed applicant persona based on responses to a series of tailored questions. Sidekick then compares the persona against a programs specific requirements and criteria. By analyzing how the persona aligns with the criteria of each opportunity, Sidekick can recommend the most suitable program, category, opportunity or notify of ineligibility. This personalized approach ensures that applicants are matched with opportunities that best fit their unique profile, maximizing their chances of success and optimizing the application process.
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Personalized Experiences enhance the application process by tailoring the submission form to applicants based on the content provided in the application process. Sidekick dynamically serves up dedicated questions and categories that are most relevant to the individual’s previously entered content. This adaptive questioning technique ensures that applicants are only presented with relevant content that align with their applicant profile, streamlining the application process. Additionally, Sidekick automatically categorizes applicants based on their responses, facilitating a more organized and efficient review process for organizations. By personalizing the application experience, Sidekick not only simplifies the submission process but also enhances the accuracy and relevance of the information collected, leading to more targeted and effective application workflow.

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Auto Screening and Ranking leverages the applicant’s persona to automate the eligibility verification process and implement a scoring system. Initially, it confirms whether an applicant meets the criteria required for each opportunity. After establishing eligibility, this feature utilizes an automated scoring mechanism that aligns with predefined characteristics of the ideal candidate such as GPA, budgets, volunteer hours, etc. This assists in the initial vetting of applicants before a more in-depth committee review.

 

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Data consolidation centralizes all data related to applicants into a single, accessible hub. Sidekick systematically compiles initial submission forms, nominations, ongoing data from recipients, file uploads with embedded viewing capabilities, and aggregates references and nominations. Additionally, it integrates all communication and results associated with each applicant. This centralized approach not only streamlines the management of extensive data sets but also enhances the accessibility and analysis of information, aiding organizations in making informed decisions efficiently.

A.I. and Plagiarism Detection

Sidekick efficiently flags instances of AI-generated content and plagiarized material within submitted applications. With Sidekick AI, you can easily identify any discrepancies and view the exact flagged content, empowering more informed decisions.

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AI Assistant for Scholarship Management visualizes how Reviewrs Sidekick AI assistant tool is used
Sidekick’s AI Detection integration scans and analyzes submitted application content to identify the use of AI assistance from tools like ChatGPT. This integration evaluates the text to determine the extent of AI-generated content and provides a percentage score of the flagged AI usage. This scoring system allows organizations to drill down into the submissions to better understand the depth of AI involvement. Armed with this data, program managers can make more informed, data-driven decisions about the authenticity and originality of the content submitted by applicants, ensuring a fair and transparent selection process.
 

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Plagiarism Detection analyzes submitted applications to identify and trace instances of copied publicly available content. This also specifies the source of the plagiarized material, whether it is a direct copy, a summary, or a modified version of the original content. For each identified instance, it provides a detailed report showing the extent of the plagiarism and the exact origin, allowing organizations to assess the authenticity of the work comprehensively. 

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Leverage detection scores to filter and analyze flagged entries to determine the average level of AI and plagiarized content used across submissions. Organizations can then identify which submissions are above or below the established thresholds. This analytical capability provides a comprehensive overview, enabling informed decisions on the integrity and authenticity of each application, ensuring a fair and transparent application allocation process.

Fair and Non-Bias Selections

Sidekick ensures a fair, non-bias, and compliant application process by incorporating tools to randomly pair applicants with review teams, redact private and confidential information, auto-tabulate selection results, and normalize selections to account for variations in an evaluator strictness or leniency.

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Streamline the process of distributing applications to review teams. Intelligently categorize applications into specific buckets based on content, applicant skills, and predefined criteria. Submissions are then automatically assigned to reviewers who are best aligned with these categories, ensuring a knowledgeable and relevant evaluation. This system also incorporates randomization to prevent bias and allows for manual overrides to address potential conflicts of interest. This automation ensures efficient, fair, and expert handling of application reviews, enhancing the overall decision-making process.

 
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Ensure a fair and unbiased review process by automatically removing any personal identifiers or confidential information from submissions before they reach review committee members. Scrub data such as names, addresses, and other sensitive details that could influence the decision-making process. By anonymizing submissions, it prevents potential biases and maintains the integrity of the selection process, allowing reviewers to focus solely on the merit and quality of the application content.

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Auto-Tabulations enhance the application review process by automatically calculating scores from comprehensive qualitative score sheets provided by reviewers. This tool aggregates these individual evaluations into a real-time leaderboard, allowing program managers to instantly view and compare the performance and standings of all applicants. This dynamic scoring system not only streamlines the evaluation process but also fosters transparency and encourages a competitive yet fair assessment environment. By providing an ongoing, accessible overview of scores, Sidekick helps organizations make informed, data-driven decisions swiftly and efficiently.

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Sidekick’s Normalized Results offers an innovative reporting tool designed to ensure fairness and consistency in the evaluation process. This feature analyzes the scoring patterns of individual reviewers or judges to identify any tendencies towards strictness or leniency. By calculating each judge’s average score, it assesses how they rated each applicant relative to their own scoring norm. These individual averages are then compared against those of other judges to highlight discrepancies and normalize the results. This detailed comparative analysis helps maintain a balanced and equitable assessment process, ensuring that each applicant is judged on a level playing field.

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The Proven Playbook to Managing Member Recognition Awards

  • Creating a proof of process.
  • The ideal nominator/nominee split workflow.
  • The right way to collect references and supplemental information.
  • Impartial distribution of nominations to review committee members.
  • Promoting a compliant, fair, non-bias selection process.
  • Engaging awardees in the post award workflow.
Get Playbook
Webinar header image for The Ultimate Playbook to Managing Awards - a step by step guide to managing member recognition awards that are efficient for program managers and engaging for participants.

Sidekick - AI Assistant for Application Management. Awards, grants, scholarships, fellowships, abstracts, and more

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