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Dilip Ittyera

Bringing the power of Enterprise Intelligence to AI | 3X Entrepreneur | ex-CTO Zensar | Built BU 0-20M+

Dilip Ittyera is a seasoned technology leader with over 37 years of experience. Currently serving as the CEO of CogniSwitch Inc., he is dedicated to developing accurate and reliable Gen-AI applications for enterprises.

He has a strong track record of translating innovative concepts into scalable solutions that bring value to customers and stakeholders.

Dilip's educational background includes a BSc in Mathematics, Physics, and Statistics from the University of Kerala, along with completing high school at Leo XIII High School.

Throughout his career, he has held various leadership positions in renowned organizations like iEngage.ai, Aikon Labs Private Limited, Zensar Technologies, Calkey Technologies Inc., and more, showcasing his diverse expertise in driving technological advancements and innovation.

As the CEO of CogniSwitch, Dilip focuses on creating digital twins of knowledge to enhance the performance of AI applications, ultimately helping enterprises unlock the full potential of AI technology.

His commitment to fostering a team of skilled professionals and leveraging tribal knowledge sets CogniSwitch apart in the tech industry, ensuring the development of robust and error-free Gen-AI applications.

Highlights

Aug 29 · linkedin

There is a screenshot floating around on how chatgpt struggled to count the # of r's in the word Strawberry. Now that doesn't happen in every conversation but again that's what is called reliability.

Both me and Giridhar L V, Nuvepro have worked long enough in enterprises that the one thing that matters when adopting AI/GenAI, atleast in enterprises is reliability.

This is also why we have taken it upon ourselves to walkthrough developers on how they can start building reliable conversational agents using knowledge graphs.

Graphs RAG has been all the rage for the last few months and in this workshop developers can actually experience the power of graph rag without having to chunk, embed, doing similarity search, choosing LLM and everything else that comes with the bloated RAG 1.0 stack.

If your team is thinking about building a genai app or has already built one, they would enjoy this hands on workshop with Nuvepro Technologies and CogniSwitch Inc. Link to register in the first comment.

Aug 16 · linkedin

🚨 If your GenAI team or product application is struggling with reliability issues, you might be focusing on improving RAG pipelines. 🔍 But here’s the truth – it’s often a data problem, not an AI problem. 💡 More developers are realizing that the "R" in RAG is crucial. This is why innovative concepts like Graph RAG are gaining traction. 🔧 However, to truly address retrieval issues, you need to start with the data itself. 🧠 Unlike humans, who intuitively build relationships between concepts and entities, machines need data in a structured, multi-dimensional format.

📊 Like a Knowledge Graph – a powerful structure that organizes information in a way that machines can understand and utilize effectively.

The answer to your RAG issues does not lie in the Graph DB that you are using. It's in the data transformation that you deploy to build the multi-dimensional structure.

#KnowledgeGraph #GenAI #GraphRAG

#AI #MachineLearning #DataScience #GraphRAG #KnowledgeGraph #GenAI #TechTrends

Dilip Ittyera
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Location

San Francisco, California, United States