Satya Borgohain is a co-founder and AI engineer with eight years of experience building agentic systems and reliable ML infrastructure, currently focused on kensa.sh and co-founding Noet to advance agentic software testing. He has led production RAG systems, large-scale vector databases, and an evals framework to ground LLMs, and previously developed multi-agent graph frameworks supporting tools, memory, planning and orchestration. His research background at Monash produced high-impact, practical ML methods—from NLP narrative extraction at scale to Bayesian neural nets and low-cost pseudo-labeling for better calibrated and interpretable models. Satya combines academic rigor with product delivery: he built production data pipelines on AWS, deployed real-time analytics apps, and shipped edge pose-estimation systems for aged care. He also brings commercial analytics experience driving Bayesian MMM and ROAS modeling for customers like SEEK and BoQ, showing an ability to translate models into measurable business impact. Based in Melbourne, he blends startup grit with research pedigree and a knack for turning agent reliability challenges into deployable software.
8 years of coding experience
6 years of employment as a software developer
Rashtrasant Tukadoji Maharaj Nagpur University
Master's degree Data Science (Advanced data analytics with Minor Thesis), Master's degree Data Science (Advanced data analytics with Minor Thesis) at Monash University
Contributions:8 commits, 5 pushes, 1 branch in 1 year 3 months
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