Our unique blended ‘tech plus touch’ approach enables us to reach women and health workers more often than is possible with traditional models, thus providing non-linear growth, while providing human touch points.

We leverage the existing frontline health worker network and health infrastructure by building strong partnerships with National and State governments, partner NGOs and health facilities.

Combined with this, capitalising on the increased usage of the mobile phones, we create at-scale mHealth programmes with proven impact. Technology also enables the creation of deeper and nuanced programming based on the degree of risk, inequity and gender disparity experienced by the woman/child.

Our interventions are founded on data and insights that are evidence-based, ensuring that every decision we make is informed by accurate, real-time information. By utilising comprehensive datasets and research-backed methodologies, we are able to pinpoint areas that require attention and tailor our approaches accordingly.

Additionally, the integration of Artificial Intelligence (AI) enhances the precision and efficiency of our processes. AI enables us to analyze complex data patterns, predict outcomes, and make informed decisions at scale, ultimately optimizing the impact of our interventions.

This combination of data-driven insights and AI allows us to address challenges in a more targeted and effective manner.

Our interventions are rooted within the Government health systems, and we understand that the health workers and officials often encounter hostile environments with power structures and entrenched patriarchal norms posing a challenge.

We use the Political Economy Analysis (PEA) framework, building a robust support system to assist the health workers in navigating these challenges, break the barriers of socio-cultural-politico-economic norms and address the existing inequities in the society to enhance the decision-making powers for women, when it comes to their health.

We place a strong emphasis on gender transformative practices and equity-based approaches to ensure fair and inclusive outcomes for all women and children.

ARMMAN uses a ‘fit for purpose‘ approach by using mHealth, to create scalable, cost-effective, nuanced and impactful programmes. In this framework, women at low risk receive comprehensive  content, utilising voice calls for those with feature phones and WhatsApp for smartphone users.

On the other hand, women at high risk or those with the greatest disadvantages, marked by limited equity, receive more tailored content with enhanced support through interactive two-way communication.

We design user-centric interventions with a ground-up approach, taking into account the limitations of the women we serve and integrating their voices through needs assessment, field-testing and feedback loops.