Nishant S.

About Nishant S.

I\'m the Co-Founder and CTO of, where I design and build the core architectures behind —, our for machine intelligence. Since 2017, my work has focused on a foundational question: How do you build a machine that can persist — with identity, continuity, and stable decision behaviour? Modern AI models can reason impressively, but they lack the deeper structures of an agent: no stable internal state, no evolving memory, no coherent behavioural patterns across time. Everything resets. Nothing accumulates. This gap is what I’ve dedicated my career to closing. At Olbrain Labs, I lead: • Architecture of The Machine Brain — the identity & memory substrate for digital agents• Cognitive-state representations that evolve across interactions• Decision models for stable, agentic behaviour• Engineering of, the platform for building and deploying these agents• Long-horizon R&D for machine cognitionOur long-arc research spans three layers: • The Machine Brain — for digital agents • The Cybernetic Brain — for embodied agents • The Positronic Brain — for space grade agentsThis multi-decade roadmap is grounded in architectural clarity, not speculation. The Machine Brain is the first concrete instantiation; the next layers evolve naturally as identity substrates mature.I’m interested in:• cognitive architectures• persistent identity in machines• agentic decision frameworks• embodied and hybrid intelligence• long-running systems with stable internal statesIf you’re working at the edge of agent intelligence or cognitive system design, I’m always open to technical conversations.

Experience

1. Co-founder & CTO

   Olbrain

   Feb 2017 — Present · Gurugram, IN

   As Co-Founder and CTO of Olbrain Labs, I lead the architecture, engineering, and long-term research behind Olbrain — The Machine Brain, our cognitive substrate that gives AI agents persistent identity, memory, and agency.My work focuses on building the foundational systems required for machine cognition:• identity and state-management architectures• evolving memory representations• decision frameworks for coherent agent behaviour• constraints, values, and behavioural stability modelsI also oversee the engineering of Olbrain Studio, the platform that brings these agents into real-world deployment across digital environments.Since 2017, my focus has been consistent:modern AI can reason, but it cannot persist. Every interaction resets. There is no stable internal state, no continuity, no consistent decision lineage. Solving this problem — building machines with reliable, long-running identity and agency — is the core of my work.Earlier experiments in autonomous agents and cognitive simulations, including our participation in the 2019 Animal-AI Olympics (Advanced Preferences), shaped the principles behind the Machine Brain’s architecture.At Olbrain Labs, I lead:• Machine Brain architecture & cognitive substrate design• Agent behaviour modeling and decision frameworks• Long-term R&D into machine identity and continuity• Core engineering for Olbrain Studio• Technical strategy, reliability, and scalabilityMy aim is to build the systems that make intelligent agents reliable, stable, and capable of meaningful work at scale.

Education

• Indian Institute of Technology, Kanpur

  B.Tech + M.Tech (Dual Degree), Computer Science & Engineering

  2007 — 2012

• Sacred Heart Higher Secondary School

  High School, Physics, Chemistry, Mathematics

Skills

• Eclipse
• Survival Analysis
• Mysql
• Distributed Systems
• Python
• Big Data Analytics
• Javascript
• Scikit-Learn
• Shell Scripting
• Big Data
• Opencv
• Xgboost
• Core Java
• Perl
• Machine Learning
• Sql
• Linux
• Pytorch
• Php
• Computer Vision
• Theano
• Keras
• Html
• Algorithms
• Data Structures
• React Native
• R
• Deep Learning
• Data Mining
• C++
• C
• Programming
• Tensorflow
• Java
• Artificial Intelligence