Why I Started Dvanjoy
Across more than a decade and a half working in education, data systems, and international development, I kept encountering the same pattern: mission-driven teams collect large amounts of data, but turning that information into timely, actionable insight is hard. While leading a nonprofit dedicated to educational equity in Malawi and studying Education, Monitoring & Evaluation (MEL), and International Development, I saw this repeatedly. The challenge wasn’t simply “more data.” It was a data systems problem.
Directors of MEL know this reality well. Data often lives in places like KoBo, DHIS2, and Excel, yet the systems needed to transform that data into decisions are complex. The result is a persistent gap:
A time tax as teams spend hours cleaning and merging files instead of analyzing impact.
A visibility lag where dashboards are disconnected from live systems and report the past rather than inform the present.
A capacity constraint, as organizations need predictive insight and sustainable pipelines, but lack the internal data science resources to build and maintain them.
Major organizations, including UNICEF and the United Nations, have called for partners to build data science capacity and accelerate the adoption of advanced analytics. Dvanjoy was founded to help answer that call.
The decision to formalize Dvanjoy, LLC in 2025 came after early tools we built for consulting projects showed how thoughtfully integrating disparate data sources could address real challenges and reveal remaining gaps. Our mission became clear: make it radically easier for mission-driven organizations to harness data to guide decisions, allocate resources, and demonstrate impact.
We designed Dvanjoy to combine cutting-edge data science with human-centered User Experience design (UX). That means addressing common concerns about black-box models and overly technical solutions that MEL or field teams won’t use. We emphasize clarity, trust, and co-creation with the communities represented in the data.
This commitment is reflected in our name. “Dvanjoy” comes from my grandparents’ names; they were entrepreneurial in the service of others. It’s a reminder to build systems that are powerful, predictable, and deeply human.
Practically, we focus on automating the data lifecycle so teams can rely on consistent, auditable flows:
Ingestion: Pull from APIs, spreadsheets, satellite imagery, and cloud buckets.
Modeling: Use machine learning and geospatial analytics where they add value.
Action: Provide real-time, intuitive dashboards for decision support.
Our approach is to connect tools organizations already use, fix issues at the source, and make donor-ready reporting routine. This reinforces the pillars that matter to MEL leaders: reduce busywork, create one trusted story, and enable early action. When we partner with organizations, we aim for visible results in months rather than open-ended pilots, help teams flag sites at risk before end-of-year reviews, and align pipelines with funder reporting frameworks so strong MEL infrastructure gets recognized.
That is why I started Dvanjoy. Mission-driven organizations deserve data systems that turn fragmented inputs into insight that is usable, timely, and responsible.