Prateek Agarwal
Co-Founder & CEO at Kainskep Solutions
About
I'm Prateek Agarwal, the Co-Founder and CEO of Kainskep Solutions. My career has been defined by a transition from core software engineering to architecting complex data platforms and now leading an engineering firm dedicated to production-grade AI. I specialize in moving AI beyond the 'demo' phase into real-world, scalable environments, particularly within highly regulated sectors like Banking and Fintech. I am deeply passionate about the shift from simple Copilots to fully autonomous agents and believe that AI success is fundamentally a data engineering challenge. I'm here to offer deep technical expertise to those looking to integrate AI with security and governance in mind, and I'm always looking to connect with CTOs and product leaders who value ownership and production-ready results over hype.
Networking
What I can offer
- ›Expertise in shipping AI into production for regulated industries
- ›Extended engineering team services
- ›Guidance on AI security and governance
- ›System architecture for scalable backend services
Looking for
- ›expanding my professional network
- ›exploring mutual opportunities in Banking, Fintech, and Enterprise SaaS
Best fit for
Current Interests
Background
Career
Started as a Software Engineer at R Systems, transitioned to Celebal Technologies where he rose from Software Engineer to Senior Software Engineer focusing on data platforms, and eventually co-founded Kainskep Solutions to lead AI engineering.
Education
Bachelor of Technology (BTech) in Computer Science, Swami Keshvanand Institute of Technology; Senior Secondary in Physics, Chemistry, and Maths, Mahaveer Public School.
Achievements
- ›Expanded Kainskep Solutions operations to Ontario, Canada
- ›Interviewed over 250 engineers to build high-ownership teams
- ›Moved AI systems from PoC to production in Banking and Fintech
- ›Developed a fully autonomous AI voice agent with CRM integration
Opinions
- AI success is a data engineering problem first and a model problem second.
- Technology is rarely the bottleneck; projects fail due to lack of trust or business impact.
- Companies should fix data for specific workflows rather than 'boiling the ocean'.
- Strongly opposes 'AI theater'—PoCs that never reach production.