Tanuja Korlepra, CTO of Bonterra – Interview Series

Tanuja Korlepra is the chief technology officer at Bonterra – a social good software company focused on powering those who power social impact with donor engagement, supporter engagement, program management, and corporate social responsibility (CSR) tech solutions.

Tanuja leads technical strategy, innovation, product development, and engineering operations at Bonterra to empower social good organizations with innovative and best-in-class technology solutions for social good. Over her two-decade career, Tanuja worked both as an Engineering and Product leader creating business value and customer impact. She formerly served as CTO at USAFacts, a nonpartisan and unbiased civic data initiative founded by Steve Ballmer, the ex-CEO of Microsoft, to empower Americans with trustworthy government data to ground debates in facts. Tanuja has extensive experience working on hyper scale environments at Amazon Web Services, Microsoft Azure, and Veritas driving innovation in areas such as Cloud, High-Performance Computing (HPC), Artificial Intelligence (AI), Data Platforms, and Data Protection for B2B and B2C SaaS, PaaS, and IaaS products and services.

Bonterra is a social-impact software company that offers an integrated suite of tools for nonprofits, foundations, corporations, and public agencies. It was formed by uniting platforms such as CyberGrants, EveryAction, Network for Good, and Social Solutions, and now supports fundraising, case management, corporate giving, and impact measurement. Today, Bonterra is one of the fastest-growing players in the “social good tech” space, serving thousands of organizations and helping them scale their mission.

Over your 21-year career spanning Microsoft, AWS, USAFacts, and Veritas, what experiences most shaped your belief in applying technology to drive social good, and how has that perspective influenced your work at Bonterra?

After working in the tech industry for over two decades, I’ve seen firsthand how technology is most powerful when it is created to serve something greater than itself. I spent most of my career working in some of the most innovative environments in tech, where I focused on helping systems scale intelligently and operate resiliently. While this work was fascinating, I continued to find myself drawn to tech that helps support bigger societal issues.

During my work at USAFacts, I developed products that make government data more transparent and accessible. It was during this period, coinciding with the rapid adoption of AI, that I began applying emerging AI tools to help solve societal challenges. That intersection of technology and social impact quickly became my passion.

At Bonterra, I’ve been able to bring that passion to life. Our mission is to help raise U.S. charitable giving from 2.5% to 3% of GDP by 2033 (“3% by ’33”), and I find this ambitious and inspiring. Every day, I get to apply my accumulated skills in engineering, product, and strategy toward empowering nonprofits and funders to thrive, using technology as a force for good.

Since stepping into the CTO role at Bonterra last year, what were your immediate priorities, and how did you approach aligning them with Bonterra’s broader mission?

When I joined Bonterra, I was already thinking about new technology to help support social good organizations, and AI was a clear solution. The company had actually laid a strong AI foundation years earlier by introducing predictive AI models in 2017. This was done through DonorTrends to help nonprofits determine optimal fundraising asks, so my team was ready to take that even further. Agentic AI stood out from the start because of its ability to transform software into autonomous digital coworkers. It doesn’t just think, it acts, and this distinction is a game-changer for social good organizations. We built AI frameworks that are secure, reliable, scalable, and reusable. The launch of our new platform, Bonterra Que, reflects that vision. Que is the first fully agentic AI platform purpose-built for the social good sector, spanning the entire ecosystem of funders, nonprofits, and supporters.

Think of it as an autonomous teammate, embedded into Bonterra’s suite of products, helping organizations raise more money, connect with funders, and accelerate impact. Importantly, it’s always human-led. The people at the heart of the organization remain in control and always make the final decision.

Internally, we’ve also embraced AI to drive productivity. We are bold about experimentation and nimble with process. My engineering team uses several tools for productivity, especially coding tools like Cursor and Claude Code to accelerate software development and streamline operations. This focus on building scalable frameworks, embedding AI for customers, while using it responsibly ourselves, gives us a wide view on evolving AI capabilities and how to balance innovation with ensuring the technology truly empowers the organizations we serve.

Bonterra describes this as the first “fully agentic AI” platform for the social good sector—how would you explain that in simple terms to a nonprofit leader unfamiliar with advanced AI?

Nonprofits have historically been handed tools built for enterprise-level companies. While these solutions offer productivity benefits, nonprofits have fundamentally different business models, and their tech stack should reflect that. Many nonprofits are adopting AI for tasks like email drafting and content creation, but the real productivity leap comes from AI agents that act. That’s where Que comes in.
Instead of just suggesting what to do or providing generalized insights, Que takes action by leveraging an organization’s data to deliver personalized recommendations and surface opportunities, always with a human decision-maker in the loop.

What we’re trying to do with Que is bring radical simplification to nonprofit technology. The goal is to make the software invisible and have the complexity live in the background. Users don’t see the underlying models or workflows; they only see and interact with an intuitive agent that quietly does the heavy lifting. This eliminates the software learning curve, giving nonprofits time back with more intuitive technology. My goal is to evolve the Software-as-a-Service model to Outcome-as-a-Service where our solutions do the majority of the heavy lifting and deliver valuable outcomes to our customers.

What types of challenges facing nonprofits today do you believe agentic AI can address most effectively, beyond the basic productivity tools they already use?

Nonprofits are under enormous pressure. Recent data shows more than half of federally funded nonprofits are experiencing instability, with 44% cutting entire programs and 39% reducing staff just to stay afloat.

Yet, nonprofit resources are more vital than ever, and these organizations are being forced to do more with less. Staff are stretched thin, overwhelmed, fighting burnout, and unable to spend time on the mission-critical work that drives community impact. They need technology that can help ease the burden by taking on tasks proactively.

Agentic AI addresses capacity constraints by completing multi-step tasks autonomously, such as matching nonprofits to funders, personalizing donor outreach at scale, or generating reports. By handling repetitive and time-intensive work, Que allows nonprofit staff to focus on what only humans can do: building relationships, fostering trust, and serving communities.

How do you ensure that autonomy is balanced with the right level of human oversight, especially when decisions impact funding, services, or vulnerable communities?

Trust is the foundation of the social good sector. That’s why Que was built to be human-led and transparent by design. It handles repetitive and time-intensive work while always allowing people to make final decisions. Users can inspect, adjust, or override any recommendation.

At Bonterra, we are committed to ethical, inclusive, and responsible AI development. That means safeguarding sensitive data, respecting privacy, and ensuring transparency, so our customers always know how their data is being used.

What were some of the biggest technical or organizational challenges your team faced in building this platform specifically for nonprofits?

Many nonprofits are wary of the security risks that come with AI, and this was something we had to navigate as we developed the platform. Organizations like shelters and clinics are working with sensitive client data, and this can make them hesitant to adopt new technology, despite productivity gains.

Part of our responsibility is showing our customers that their data isn’t at risk simply because they’ve adopted technology. We treat sensitive information with the highest level of care. We have built technology that is grounded in strong operational controls and industry practices, and as a result, we have created technology that our customers can trust.

Many nonprofits operate with limited budgets—how is Bonterra thinking about accessibility, affordability, and long-term sustainability for this technology?

Many nonprofits operate with limited budgets, so accessibility, affordability, and sustainability are core considerations in how Bonterra builds technology. Our solutions are designed with accessibility in mind through our design system, Stitch, which prioritizes inclusive design from the start. Stitch is built to meet web content accessibility guidelines, 2.2 AA standards, and all work undergoes internal quality assurance by both designers and developers. To further ensure transparency and accountability, Bonterra is also completing a voluntary product accessibility template.

Affordability is another cornerstone of our approach. Bonterra Que provides free best practice coaching that draws on decades of experience, proven methods, and sector-wide insights, ensuring nonprofits can access meaningful expertise at no additional cost.

Finally, Bonterra is deeply committed to sustainability and the responsible use of AI. We use foundation models only for inference, not training, which significantly reduces the carbon footprint of our AI usage. Our infrastructure runs on Amazon Web Services (AWS), which is 3.6 times more energy efficient than traditional data centers and on track to achieve 100% renewable energy by 2025.

Together, these commitments ensure that Bonterra’s technology remains powerful and innovative while being accessible, affordable, and environmentally responsible for the long term.

What kinds of outcomes or success metrics are you most interested in seeing from early adopters of the platform?

Over the next few months, we’ll pay special attention to which tasks Que is taking on and how effectively it can complete them.

For example, the Donor Segmentation feature generates supporter segments using natural language inputs based on giving behavior, interests, and engagement history. It will be interesting to see how engagement rates have increased for organizations using this tool. With the Grant Matching capabilities, which match funders and nonprofits based on their needs, I’d like to see a positive increase in the number of partnerships that are successfully established because of the tool.

But the metric that matters most is time saved. Every hour that nonprofits spend on administrative work is an hour they cannot devote to building relationships, delivering services, or driving their mission forward. Our goal is to have Que lead repetitive, time-consuming tasks so organizations can free their staff to focus on uniquely human work. We obsess over our customers and are working in close partnerships with many. Their feedback will continue to shape our roadmap.

As nonprofits adopt agentic AI, how do you anticipate staff roles and day-to-day workflows will evolve—will the technology primarily augment their work, or transform it more fundamentally?

Nonprofit workers are currently overloaded and often do the work of multiple people, but the goal of introducing AI to the sector is not to replace nonprofit workers. In fact, these organizations are so resource-constrained and understaffed that AI simply can’t be a replacement.

We want AI to take the tasks off workers’ plates that they simply don’t have time for. If a nonprofit employee had to conduct in-depth personalized outreach to 50 potential donors a day, was expected to build out a fundraising plan and write a new grant proposal, burnout and a decline in work quality are inevitable. AI can help alleviate these tasks by writing email drafts or putting together a grant outline. These are the types of jobs that agentic AI can handle, with the goal of allowing nonprofit workers to focus on the work that cannot be done by technology.

Looking ahead, what do you see as the most important ways Bonterra’s agentic AI can evolve over the next three to five years to further support organizations in the social good sector?

In fundraising, Que will expand into real-time campaign optimization, SMS and event creation, workflow automation, and automated reporting. In case management, it will support eligibility assessments, caseload prioritization, and data validation. And in impact management, Que will streamline collaborative reporting across nonprofits and funders, making it easier to prove and scale outcomes. We are going to build all these capabilities with security, scalability, and ethics in mind. While the capabilities will continue to get better, we will also scale in a way customers are able to parallelize multiple tasks for greater efficiency.

Our long-term vision is to fuel what we call the Generosity Generation, where data, insight, and human connection converge to unlock greater giving. By embedding AI across fundraising, grantmaking, CSR, and case management, Bonterra is leading a movement that accelerates impact and builds trust at scale.

Thank you for the great interview and for leading the creation of technology that’s redefining how social impact is achieved, readers who wish to learn more should visit Bonterra.