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Beyond the Hype: Pranav Pawar On How to Build Reliable AI in Production

Beyond the Hype: Pranav Pawar On How to Build Reliable AI in Production

Published 2 months, 2 weeks ago
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This story was originally published on HackerNoon at: https://hackernoon.com/beyond-the-hype-pranav-pawar-on-how-to-build-reliable-ai-in-production.
How engineer Pranav Pawar builds reliable, scalable AI systems for real-world production—from healthcare automation to marketing agents at Kalos.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai-infrastructure, #ml-models, #reliable-ai-systems, #ai-in-production-engineering, #multi-agent-ai-orchestration, #healthcare-ai-automation, #b2b-marketing-ai-agents, #good-company, and more.

This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com.

This piece explores how engineer Pranav Pawar builds AI systems that survive real-world complexity. From deal-sourcing at Bain to healthcare automation and now orchestrating multi-agent marketing systems at Kalos, Pawar focuses on reliability, verification, and long-term scalability. His work shows how AI becomes useful only when built to deliver consistently in production.

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