Leveraging AI to Enhance Business Processes

Please join us for our March Meetup focused on leveraging AI to enhance everyday business processes. We will serve food at 6pm and presentations will begin at 6:30p.m. We will present 2 topics at this event:

• Advancing OCR with LLMs: From Extraction to Reasoning by Sumedh Khodke
• The GenAI Journey: Lessons from Turning Concepts into Real-World Solutions by Suresh Thalluri

Sumedh Khodke is a Machine Learning and AI Engineer at Lean Innovation Labs specializing in NLP, deep learning, and scalable AI solutions. With expertise in building large-scale ML pipelines and RAG systems, he has developed high-performance models for real-world applications. Sumedh has experience optimizing LLMs for information retrieval, OCR, document understanding, and multimodal AI, enhancing efficiency in extraction and reasoning. He has contributed to AI research, delivered technical sessions on machine learning, and actively engages in advancing AI-driven automation within the ML community.

Suresh Thalluri is an entrepreneur, founder, and investor with a knack for building and launching products — from GenAI-powered no-code platforms to embedded data analytics solutions. As the CEO of Lean Innovation Labs, he leads a team of innovative engineers, helping commercial and federal clients navigate their digital transformation journeys. A passionate technologist and avid coder, Suresh loves exploring how GenAI can tackle problems in new ways and reshape how we build apps. Beyond his work, Suresh is an outdoor enthusiast — avid hiker and runner — and is deeply committed to giving back to the developer and startup community.

Adding in Zoom link here for those of you not able to attend in person: Solution Street is inviting you to a scheduled Zoom meeting.
Topic: NOVA SART Meetup Event
Time: Mar 20, 2025 06:00 PM Eastern Time (US and Canada)
Join Zoom Meeting
https://us06web.zoom.us/j/82371481328?pwd=aeHCZJRghq8AXG9Tihga8W7teVGwqH.1
Meeting ID: 823 7148 1328
Passcode: 225947
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Meeting ID: 823 7148 1328
Passcode: 225947
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