Othor AI

During my time leading the Labs division at a fast growing wellfunded startup in 2023, I was entrusted with a critical mission: to uncover why the adoption of our business intelligence tool was limited and to drive a culture of data-centric decision-making across the organization. Through extensive user interviews and research, I discovered a significant gap in the field of business intelligence. While we were data-rich, the insights simply weren't reaching the right people at the right time---they were often lost within complex workflows. Traditional BI processes were slow, fragmented, and involved multiple teams working in silos. Even simple report changes could take weeks to complete, significantly impacting our agility. The issues didn't stop there. These traditional BI solutions were costly, offered limited value, and required technical knowledge to customize, creating accessibility barriers for non-technical users. Despite our best efforts, solving these challenges within the company was met with limitations, making it clear that inhouse development of a scalable, rapid BI solution was difficult to achieve in a fast-growing organization. After leaving my last company in 2024 to pursue a Doctorate in Generative Intelligence at Golden Gate University, San Francisco, I began to see the transformative potential of Generative AI in business intelligence. Building on my experience as Founder & CEO of Foradian, I envisioned a new approach to BI---one that would deliver real-time, context-aware insights without the delays, costs, or technical barriers of traditional tools. And so, Othor.ai was born with a clear mission: to bring actionable, context-rich insights directly to decision-makers, transforming BI into a powerful, agile, and accessible tool for every organization.

As the founding engineer of Othor.ai, I've tackled these challenges head-on while building our solution. One of our biggest technical achievements was developing a robust real-time processing architecture that seamlessly integrates with existing data infrastructure while maintaining sub-second latency. The most rewarding breakthrough came when we cracked the contextual understanding piece - our system now intelligently processes both structured and unstructured data sources, automatically surfacing relevant insights based on the user's role and historical interaction patterns. We've managed to eliminate the traditional trade-off between power and accessibility by building a natural language interface backed by a sophisticated query optimization engine. Totally agree with Unni's observations about the limitations of traditional BI tools. It's why we focused heavily on building a scalable, containerized architecture that can handle enterprise-level data volumes while remaining incredibly responsive. Our approach to handling real-time data streams while maintaining context has been particularly effective in eliminating those weeks-long reporting delays you mentioned. Would be happy to share more technical details about how we solved these challenges. The journey from concept to production has been incredibly rewarding!

"Congratulations on the launch of Othor AI! Wishing you all the best