The Future Of Grant Management Is Here.
Meet “Sidekick”, the industries first AI assistant for grant management that incorporates intelligent automation and A.I./Plagiarism detection to streamline processes, improve decision-making, and elevate the grant experience.
5 ways AI will transform grant management
Discover how AI will impact grant management to streamline processes, ensure fairness, and optimize resources. Learn how automated systems match applicants to grant opportunities, create efficiencies, and check for AI generated grant writing.
Intelligent Automation
Sidekick leverages intelligent automation to create a personalized experience for participants, ensuring quality data collection, opportunity visibility, and consolidated workflows.
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 grant 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.
Personalized Experiences enhance the grant application process by tailoring the submission form to grant 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 grantee profile, streamlining the application process. Additionally, Sidekick automatically categorizes applicants based on their responses, facilitating a more organized and efficient review process for grant providers. 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 grant program.
Data consolidation centralizes all data related to grant applicants into a single, accessible hub. Sidekick systematically compiles initial submission forms, ongoing data from grant 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 grantmakers in making informed decisions efficiently.
A.I. and Plagiarism Detection
Sidekick efficiently flags instances of AI-generated content and plagiarized material within grant applications. With Sidekick AI, you can easily identify any discrepancies and view the exact flagged content, empowering more informed decisions.
Sidekick’s AI Detection integration scans and analyzes submitted grant 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 grantmanagers to drill down into the submissions to better understand the depth of AI involvement. Armed with this data, grantmakers 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.
Leverage detection scores to filter and analyze flagged entries to determine the average level of AI and plagiarized content used across submissions. Grant makers 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 grant allocation process.
Fair and Non-Bias Selections
Sidekick ensures a fair, non-bias, and compliant grant by incorporating tools to randomly pair grant 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.
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.
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.
The experience your deserve
The Proven Playbook to Managing Grants
- Creating a proof of process.
- The ideal application structure for data collection and safeguarding applicant data.
- The right way to collect references and supplemental information.
- Impartial distribution of grant applications to review committee members.
- Promoting a compliant, fair, non-bias selection process.
- Engaging grantees in the post grants awardee workflow.
