Haqdarshak turned welfare discovery into a paid job for rural women

India runs thousands of welfare schemes, yet the poorest citizens often never receive them: in Uttar Pradesh, over US $1.3 billion in minority-welfare funds went unspent between 2013 and 2017, and in Karnataka only 2.44% of a US $735 million workers' welfare corpus was used — largely because eligible people did not know the schemes existed or how to apply.

Founded in 2016 by Aniket Doegar, Haqdarshak attacked the information gap as a two-sided problem. First it did the unglamorous work: visiting government departments to digitize scheme rules, eligibility criteria and application processes into an app in 11+ vernacular languages, behind a proprietary 'scheme eligibility engine' that matches a citizen's profile to entitled schemes.

The second half of the model is human. Haqdarshak trains rural women as agents who go door to door, screen families, file applications and chase government offices until benefits land. Citizens pay the agent a small fee directly — typically earning the agent Rs 3,000–5,000 a month — so the channel is self-financing and runs on word-of-mouth trust, which rural India values more than any campaign.

By 2022, when Doegar won the Schwab Foundation's Social Entrepreneur of the Year India award, Haqdarshak operated in 24 states, had trained over 22,800 agents, and reported unlocking benefits worth Rs 4,000 crore for more than 20 lakh (2 million) families and 35,000 micro businesses.

A paid neighbor, not a poster, delivers the entitlement

The failure was informational, not fiscal — money existed, so awareness design, not new spending, was the lever.

A citizen-paid agent converts distribution from a cost center into someone's livelihood, making it self-sustaining.

Digitizing scattered scheme rules into one eligibility engine made a thousand-program bureaucracy queryable by a village agent.

Door-to-door neighbors carry trust that posters, radio and portals never achieved in low-literacy areas.

When a benefit fails to reach people, the missing piece is often a trusted human with an incentive to finish the paperwork — build the agent's income into the model and distribution funds itself.

Haqdarshak kept scaling: it later curated a repository of some 7,000 schemes in 12+ languages, attracted investment from Acumen and HiiL's Innovating Justice Fund, and reported reaching over 7.6 million families — while extending the same agent model to India's 63.5 million micro businesses.