Your agents can build almost anything. Can you tell which build is right?
We help you find the right one before it reaches real users.
Dr. Nishant Sinha — CMU PhD, ex-IBM Research, 20+ years building production AI systems
Spinning up a RAG or agentic search system isn't the hard part anymore — an agent can wire up an agentic search pipeline, demoable in an afternoon. What doesn't get any easier is knowing whether it actually works: whether it retrieves the right passage from your documents, handles the questions your users actually ask, and holds up once real traffic arrives. That's the gap where most of these projects quietly fail.
OffNote helps teams design, review, and de-risk real AI systems across RAG, agents, search, voice, and enterprise workflows.
Code comes and goes. What you learn from evaluating it is the only thing that compounds.
Short live sessions on harness design, search with agents, and low-latency voice applications.
Practical notes on real AI systems: what works, what breaks, and what it costs.
Nishant's contributions were crucial in laying the foundation for our AI search and recommendation system. He was not only a strategic thinker but also a professional who added significant value to our project. His thoughtful approach and commitment to excellence greatly enhanced our team's capabilities and drove us towards innovative solutions.
Nishant is incredible to work with. He is a fount of machine learning wisdom and knowhow. His involvement with our project was instrumental in taking it to new heights.
Nishant consistently demonstrated a deep understanding of machine learning and engineering principles, which was evident in the insightful and challenging questions he posed during our meetings.
Depending on how well-defined the problem is, engagements take one of two forms.