NPthrive
Ready for your Organisation to Thrive in the
Non-Profit World?
We are NPthrive, a technology platform focused on Institutional Capacity Development built specifically to help early stage, mid-level and advanced grassroot organisations, NGOs and other non-profit ventures who dream to effectively manage and grow their organizational portfolios.
We use Machine Learning and other technologies to encode hard-earned 20+ years of wisdom in organizational systems learning and institutional capacity leadership into an automated expert system which helps organizations get to the next level of performance.
As a solution to the difficulty of accessing in-person consultants to get the right advisory expertise due to the COVID-19 pandemic and other factors, this platform will help you run your non-profit and thrive, all from the comfort of your home, from anywhere in the world through a four stepwise process as detailed below.
A 4 Step Process to Institutional Capacity Development:
- An Online-based 360-Degree Organizational Self-Assessment
- An Automated Report Generation Detailing Strengths and Identified Gaps
- Generation of Actionable Recommendations for Adaptable Tools, Policy Manuals and Guidelines Available on NPthrive Platform
- Tracking and Evaluating Progress
Whetever Level of Growth Your Nonprofit is at, Our Curated Adaptable Tools, Manuals and Policy Guidelines Help With Capacity Areas Like:
- Strategy Development
- Board Governance
- Financial Management
- Human Resources Management
- Fundraising and Resource Mobilization
- Partnership and Communications Management
- Monitoring and Evaluation
- Risk Management
- Grants Management
- Cost Allocation Guideline Setting
- Reserve Policy Guideline Setting
Dr. Obed Kabanda
Doctor of Organizational Learning and Leadership with over 20+ years experience in non-profit. An internationally recognised and awarded expert in the field of Capacity Development for non-profit organizations
Tomas David Ye
Mathematician and Software Engineer with over 5 years of working experience in software technology and 3 years of Machine Learning and Applied Science experience at Amazon.
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