+26% Increase in Grant Submission Pace
Client: Philanthropy | Nonprofit Organization
Tools: AI Research Agents, Microsoft Copilot, AI-Assisted Grant Evaluation
The Challenge
Identifying and evaluating grant opportunities was a time-consuming process for HumanGood’s philanthropy team. Staff needed to research potential funders, determine eligibility, and assess which opportunities were worth pursuing.
The organization wanted to increase grant applications by 3x, but manually researching and evaluating opportunities limited the team’s capacity to identify and pursue additional funding.
The Solution
Developed two Copilot AI agents to streamline grant discovery and evaluation, helping the team move from manual research to a more systematic, AI-assisted workflow.
Agent 1 — Grant Discovery & Research
Researched potential funding opportunities across multiple sources.
Gathered relevant grant details, including eligibility requirements, funding priorities, and application criteria.
Organized findings to make opportunities easier to review and compare.
Agent 2 — Grant Evaluation & Prioritization
Evaluated research results against six predefined eligibility and relevance criteria.
Scored opportunities to help identify grants most closely aligned with the organization’s qualifications and funding priorities.
Produced structured results to support faster review and more informed decisions about which grants to pursue.
The Impact
26% Increase in Grant Submission Pace
HumanGood reported a 26% increase in its monthly grant submission rate compared with 2025, with additional submissions anticipated before year-end.
Beyond the increase in submissions, the organization reported stronger research practices, greater adoption of AI in daily operations, and a more proactive approach to pursuing funding opportunities.
Business Value
Transformed a large volume of scattered grant information into organized, actionable research that helped the philanthropy team identify promising opportunities and focus its efforts where they mattered most.
Rather than manually researching and evaluating every potential funder, the team gained a repeatable AI-assisted process for discovering opportunities, assessing eligibility, and prioritizing grants.
The project’s lasting value extended beyond the agents themselves, helping establish AI skills and practices that became part of the team’s everyday work.
case studies
From 131 M365 Product Updates to Actionable Intelligence with Notion AI
Client: Mellonhead | AI Education & Consulting
Tools: Notion, Notion AI Agents, Microsoft 365 Roadmap
The Challenge
Microsoft 365 continuously introduces new features, making it difficult for a small AI consulting team to stay current, identify which capabilities matter to clients, and keep training materials accurate, while running a business.
Mellonhead needed a systematic way to track product updates, prioritize features for hands-on testing, and determine how new capabilities should be incorporated into its existing training curriculum.
The Solution
I designed and built a connected, three-agent AI workflow in Notion to streamline feature discovery, research, and curriculum analysis.
Agent 1 — Feature Discovery & Prioritization
Ingested (initially, this is ongoing) 131 Microsoft 365 features from Microsoft’s product roadmap into a centralized Notion database.
Organized features by application, release timing, description, and relevance.
Categorized features as TEST, WATCH, or SKIP, identifying 27 features for hands-on evaluation.
Agent 2 — Feature Research & Learning
Researched features prioritized for testing.
Gathered supporting resources from Microsoft documentation, YouTube demonstrations, and third-party articles.
Organized findings to help the team understand new capabilities and prepare for hands-on testing.
Agent 3 — Curriculum Analysis & Recommendations
Cross-referenced emerging Microsoft 365 capabilities identified through roadmap monitoring against Mellonhead’s existing training curriculum.
Evaluated how new features affected current lessons, instructions, and training content.
Identified 15 curriculum sections requiring review or revision and recommended specific content updates.
The Impact
131 Features Tracked | 27 Prioritized for Testing | 15 Curriculum Sections Flagged
In one glance, each team member could identify the feature, the importance, the main function and the change to curriculum.
The three-agent workflow established a repeatable process connecting product discovery, technical research, and curriculum development.
By centralizing Microsoft 365 updates and using AI to evaluate their relevance, Mellonhead gained a structured way to prioritize new capabilities, support internal learning, and identify where client-facing training materials needed updating.
Business Value
Transformed a high volume of constantly changing information into a reusable AI-assisted system that helps a small consulting team keep pace with evolving technology while maintaining relevant, up-to-date educational content.
