Philanthropic funds often focus on high-level decision-making, outsourcing data processing and impact measurement to grantees. This approach tends to result in impact assessments that are measured against expected outcomes rather than actual impact. The data collected is inevitably biased towards the initial promises, obscuring important insights that could enhance the fund's effectiveness in pursuing its cause. Due to limited funding and the high costs of IT infrastructure and talent, NGOs often overlook the value of modern tech solutions, despite their clear benefits for funders and impact assessment.

By receiving comprehensive and holistic in-house technological support and introducing cutting-edge technologies, a fund can streamline its grantmaking processes at all levels. This includes forecasting potential outcomes, improving decision-making, and collecting, processing, and analyzing data from projects in real-time.

Introducing new technologies allows funds to dramatically reduce the costs associated with measurement, as machine learning can forecast and extrapolate data, enabling real-time course corrections to optimize fund allocations. This not only enhances efficiency but also ensures that the funds are utilized in the most impactful way possible.