As artificial intelligence moves from experimentation to dependable execution, its potential to reshape the social sector is becoming increasingly tangible. With the launch of AI for Cause, Neural Arc is positioning enterprise AI not as a luxury reserved for large institutions, but as foundational infrastructure for nonprofits working under persistent resource constraints. In this conversation, Aniket Tapre, Founder and CEO of Neural Arc, reflects on the structural gaps that prompted the initiative and why this moment marks a turning point for responsible, outcome-driven AI adoption in the development ecosystem.
Tapre outlines how Helium AI’s unified intelligence platform, powered by Adaptive Intelligence Memory (AIM), Mantis, and Prism, is designed to reduce operational friction while strengthening fundraising, research, reporting, and outreach. Moving beyond efficiency metrics, he explains how capability-led CSR can enable nonprofits to build long-term resilience, embed ethical AI into daily workflows, and scale impact with confidence. The interview offers a clear view of how enterprise AI can evolve into core infrastructure for the social sector, provided it is built with accessibility, governance, and equity at its core.
Scroll down to read the full interview:
Q. What gap did you observe in the nonprofit ecosystem that led to the launch of the AI for Cause initiative, and why was this the right moment to introduce it?
A. Nonprofits operate in increasingly complex environments but remain constrained by manual processes, fragmented knowledge, and limited access to advanced intelligence systems. AI for Cause was launched to address this structural capability gap by providing enterprise-grade AI as a foundational operating layer. This is the right moment because AI has matured from experimentation to dependable execution, enabling real-world impact when applied responsibly and contextually.
Q. Many NGOs struggle with limited resources and high operational overheads. How can enterprise-grade AI meaningfully reduce these constraints without adding complexity?
A. Helium AI reduces overhead by acting as a unified intelligence layer rather than a collection of tools. Its Adaptive Intelligence Memory, AIM, continuously learns organizational context, decisions, and data, eliminating repetitive work. NGOs interact through natural language while the platform orchestrates complexity in the background, delivering outcomes without increasing operational burden.
Q. AI for Cause positions AI as an equalizer rather than a privilege. How do you ensure that smaller or less tech-enabled nonprofits can realistically adopt and benefit from the platform?
A. Helium AI is designed for accessibility. AIM provides contextual understanding without manual configuration, Mantis enables one-click creation of professional presentations and reports, and Prism allows nonprofits to generate high-quality visual content without design teams. Combined with guided onboarding, this ensures adoption even for organizations with minimal technical capacity.
Q. Could you share specific use cases where Helium AI is expected to deliver the most immediate and measurable impact for nonprofits, such as fundraising, research, or outreach?
A. In fundraising, AIM supports donor research and personalized engagement at scale. For research and policy work, Helium synthesizes large datasets into actionable insights. Mantis accelerates impact reports, grant proposals, and board presentations, while Prism enables compelling campaign visuals and outreach material. These use cases deliver immediate gains in speed, quality, and reach.
Q. The program offers a 12-month engagement framework. What does successful implementation look like at the end of this period for a participating nonprofit?
A. After twelve months, a successful nonprofit operates with AI embedded into daily workflows. AIM functions as an institutional memory, Mantis standardizes high-quality reporting and communication, and Prism supports consistent visual storytelling. The organization becomes faster, more data-driven, and operationally resilient without external dependency.
Q. How will you measure and track the social impact generated through AI for Cause beyond efficiency gains and time savings?
A. Impact is measured through outcome-driven indicators such as increased funds raised, improved donor retention, expanded beneficiary outreach, higher-quality reporting, and faster program execution. These metrics directly link the use of AIM, Mantis, and Prism to tangible mission outcomes rather than internal efficiency alone.
Q. Responsible AI adoption is a growing concern, particularly in sensitive sectors such as healthcare, human rights, and social welfare. How does Helium AI address issues of data security, ethics, and compliance in nonprofit deployments?
A. Helium AI is built with enterprise-grade security, strict data isolation, and compliance-first architecture. Nonprofit data is never used to train models. AIM ensures traceable and auditable intelligence workflows, while governance controls support ethical deployment in sensitive environments.
Q. What criteria were prioritised while selecting nonprofits for the program, and why was scalability and digital readiness an important consideration?
A. We prioritised mission integrity, leadership commitment, ethical alignment, and readiness to operationalize AI. Scalability and digital readiness ensure that AIM-driven learnings, Mantis-generated assets, and Prism-powered communication can be replicated across programs and regions for sustained impact.
Q. From a CSR and ESG perspective, how do initiatives like AI for Cause help technology companies move from philanthropy-driven CSR to capability-led impact creation?
A. AI for Cause enables long-term capability building rather than short-term funding. By equipping nonprofits with AIM for intelligence, Mantis for structured communication, and Prism for storytelling, CSR investments translate into durable, self-sustaining impact aligned with ESG principles.
Q. Looking ahead, how do you envision the role of enterprise AI evolving in the social sector over the next five years, and what responsibility do AI companies carry in shaping that future?
A. Enterprise AI will become core infrastructure for the social sector. Platforms like Helium will function as digital operating systems for nonprofits. AI companies have a responsibility to ensure accessibility, ethical governance, and inclusive design so that technological progress results in equitable societal outcomes.
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