Apoorva Kumar, Co-Founded Inspeq AI along with Ramanujam Macharla Vijayakumar . He brings a wealth of experience from esteemed roles at tech giants including Microsoft, Amazon Web Services, SAP, and Informatica. With a passion for innovation in artificial intelligence (AI), Apoorva co-founded Inspeq AI to address critical challenges in AI reliability and security. His journey from leading tech corporations to pioneering AI evaluation solutions underscores his commitment to reshaping the future of AI technology. In this exclusive interview with Startup77, Apoorva Kumar shares his visionary insights on revolutionizing AI reliability and security through Inspeq AI’s cutting-edge technology.
What inspired you and your team to transition from established roles at Microsoft, AWS, SAP, and Informatica to founding Inspeq AI? Could you share the pivotal moment or vision that led to this decision?
Apoorva Kumar: I always wanted to build a globally impactful startup aligned with my passion. There is only one life, and I didn’t want to regret later that I did not try. After experiencing the issues with LLMs firsthand in companies like Microsoft and Meta, my friend Ram and I thought it was a great problem to solve. We deep dived into it and gathered proof points through customer discovery, which gave us the confidence to leave our well-paying jobs and go full-time into building Inspeq. Also, Ram and I have a lot of mutual trust, and you can only make such decisions if you have confidence in your partner.
Inspeq AI focuses on evaluating, optimizing, and monitoring LLM apps like AI Conversational Bots and Content Generation Agents. How do your proprietary metrics differentiate Inspeq AI from other platforms in the market?
Apoorva Kumar: Inspeq AI’s unique and transformative platform doesn’t use LLMs as judges. Almost 95% of our competition uses LLMs for evaluating LLMs. We have used cutting-edge research in the field of NLP and statistical modeling to develop metrics for our platform. This research has helped us achieve better, faster, and cheaper results. Our unique Go-to-Market (GTM) strategy also differentiates us from our competitors.
Your platform offers both a low-code desktop application and a pro-code SDK. What considerations went into designing these dual functionalities, and what benefits do they provide to your users?
Apoorva Kumar: The pro-code SDK was developed for technical personas like developers and data scientists. They can evaluate AI apps at scale with just a few lines of code. The low-code version of the product was built for non-technical personas like Project Managers and Marketers, as we believe that Generative AI (GenAI) is already in the hands of business users as well.
Could you walk us through a typical scenario where Inspeq AI has significantly improved the efficiency or performance of an AI application, showcasing the platform’s impact on real-world projects?
Apoorva Kumar: Inspeq AI has drastically reduced human efforts and provided consistency in LLM outputs. One of our customers used to deploy human evaluators who took 2 days to manually evaluate their AI app’s output. Now, with Inspeq, they have reduced this process from days to hours and are able to identify 90% more hallucinations.
Generative AI has been transformative across industries. Could you explain why understanding hallucinations in AI is crucial, and how Inspeq AI addresses these challenges in its evaluations?
Apoorva Kumar: We’ve seen cases like DPD in the UK, where a bot started cursing consumers, causing reputational damage to DPD as a brand. Snapchat’s bot provided inappropriate recommendations to minors on booze and sex. These incidents underscore the urgent need for reliable AI.
Inspeq AI’s evaluation framework can catch up to 90% of hallucinations and improve model accuracy by up to 80%. Before deployment, customers can identify inaccuracies and inconsistencies in their outputs. Moreover, real-time guardrailing can deflect any malicious outputs.
Security is a critical concern in AI applications. What are some best practices Inspeq AI recommends for safeguarding AI systems, especially in terms of data privacy and integrity?
Apoorva Kumar: Inspeq’s evaluation framework provides security metrics for detecting prompt injection attacks, jailbreaking, and other OWASP attacks. Moreover, Inspeq can evaluate customer data without extracting it from their on-premise systems, ensuring data privacy and integrity.
In the evolving field of Generative AI, how does Inspeq AI position itself against competitors? What unique advantages or capabilities does your platform offer compared to other solutions in the market?
Apoorva Kumar: Our unique framework provides more accurate, faster, and cheaper results because we don’t use LLMs as judges. Additionally, our GTM strategy, focused on enterprises, provides a significant competitive advantage.
As you expand Inspeq AI’s reach, what are your strategies for maintaining innovation and staying ahead of technological advancements in AI evaluation and optimization?
Apoorva Kumar: We partner closely with academia such as NUI Galway, University of Liverpool, etc., to stay updated with academic advancements in this field. We also hire researchers passionate about applied AI principles. Additionally, we stay informed about emerging startups in the Gen AI sector.