Guna Optimization: A Sāṅkhya Physics for Neural Networks
How Sāṅkhya's concept of the three cosmic Guṇas (Sattva, Rajas, Tamas) maps to hyperparameter optimization, learning rates, regularization, and convergence.
Founder · Engineer · Bar-Licensed Lawyer · Vedanta Student
I build tuning forks
for noisy systems.
AI Reliability Engineering is the discipline of finding truth references. Founder of Qualixar — seven shipped open-source instruments, seven arXiv preprints, and a daily dawn study of Vedanta and Sāṅkhya validation models.
Creator of Qualixar
0+
Years in IT
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Industries
0
arXiv Preprints
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Live Instruments
Philosophy & Impact
Ancient logic for modern agency.
We model systems using principles from Indian epistemology. Classical Indian philosophy was designed for a single goal: verifying truth references in dynamic, non-deterministic environments.
Sāṅkhya Darśana
Guna Optimization
Balancing the three cosmic Guṇas (Tamas/inertia/regularization, Rajas/learning rate/momentum, and Sattva/convergence) to tune neural network hyperparameters.
Kashmir Shaivism
Prakāśa & Vimarśa
Viewing static weights (Prakāśa) as latent potential, animated by dynamic runtime self-reflection loops (Vimarśa) and iterative token generation (Spanda).
Advaita Vedanta
Pramāṇa Epistemology
Applying classical validation instruments (Pratyakṣa, Anumāna, Śabda) to build formal assertions and reliability verification checks for agentic runtimes.
System Impact
Read the Blog Essays →Verification Runtimes
Translating theoretical metaphysics into production code. Real-time contracts, assertions, and test pipelines.
The Qualixar Suite
So I built the tools.
Research-backed instruments for building, testing, securing, and governing autonomous AI agents. 7 live · 3 in the forge · more in research.
Livecontracts
AgentAssert
Design-by-Contract for AI Agents
Formal specification and runtime enforcement of behavioral contracts for autonomous AI agents. Prevents drift, ensures compliance, enables composition.
Livesecurity
SkillFortify
Supply Chain Security for AI Agent Skills
Static analysis, behavioral sandboxing, and cryptographic attestation for the AI agent skill ecosystem. Detects malicious skills before they execute.
Livememory
SuperLocalMemory
Information-Geometric Memory for AI Agents
Local-first AI agent memory with mathematical foundations. 74.8% on LoCoMo without cloud dependency — highest local-first score reported. Fisher-Rao retrieval, sheaf cohomology, Langevin lifecycle. EU AI Act compliant.
Livecommunication
SLM Mesh
Peer-to-peer communication layer for AI coding agents
P2P agent communication with 8 MCP tools. Agents discover each other, send messages, share state, and lock files. Works with any MCP-compatible agent. SQLite + UDS for <100ms delivery. 480 tests, 100% coverage.
Liveinfrastructure
SLM MCP Hub
The World's First MCP Gateway That Learns
One hub process, every MCP server, every AI client. 430+ tools exposed through 3 meta-tools — 79% fewer processes, 150K tokens saved per session. Federated tool discovery with shared cache, cost telemetry, and retrieval learning.
Liveorchestration
Qualixar OS
AI Reliability Engineering — The Universal Runtime for AI Agents
Orchestration runtime of the Qualixar AI Reliability Engineering platform. 13 execution topologies (sequential, parallel, debate, mesh, hybrid, and more), Forge AI auto-design, adversarial judge pipeline, cost-quality-latency routing. 2,936 tests passing. Paper on arXiv.
Livetesting
AgentAssay
Regression Testing for Non-Deterministic AI Agents
Token-efficient stochastic behavioral testing framework purpose-built for non-deterministic AI agent workflows. Part of the Qualixar AI Reliability Engineering platform.
Coming Soonbenchmarks
Project Echo
Multi-agent communication degradation benchmarking.
Coming soon
Researchtesting
Project Sentinel
Reliability analysis for AI-generated code.
In development
Researchobservability
Project Rewind
Time-travel debugging for autonomous agents.
In development
Researchtesting
Project Aurora
Chaos engineering principles applied to AI agent systems.
In development
Researchobservability
Project Bridge
Migration engineering across agent frameworks.
In development
Researchcontracts
Project Nexus
Composition testing for agent pipelines.
In development
Research
And proved it with math.
Published on arXiv. Formal methods, security, and memory for AI agent systems.
arXiv:2604.04514
SuperLocalMemory V3.3: The Living Brain — Biologically-Inspired Forgetting, Cognitive Quantization, and Multi-Channel Retrieval for Zero-LLM Agent Memory Systems
cs.AI
→ Biologically-inspired forgetting, cognitive quantization, multi-channel retrieval
Read on arXiv →arXiv:2602.22302
Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents
cs.AIcs.MAcs.SE
→ 1,980 experiment sessions across 7 models
Read on arXiv →arXiv:2603.00195
Formal Analysis and Supply Chain Security for Agentic AI Skills
cs.CRcs.AIcs.SE
→ 675 tests, 8 novel contributions
Read on arXiv →arXiv:2603.14588
SuperLocalMemory V3: Information-Geometric Foundations for Zero-LLM Enterprise Agent Memory
cs.AIcs.IRcs.LG
→ 74.8% on LoCoMo (zero cloud) — highest local-first score reported
Read on arXiv →arXiv:2603.02240
SuperLocalMemory V2: Privacy-Preserving Multi-Agent Memory with Bayesian Trust Defense Against Memory Poisoning
cs.AIcs.SE
→ Local-first architecture, Bayesian trust defense against memory poisoning
Read on arXiv →arXiv:2603.02601
AgentAssay: Token-Efficient Regression Testing for Non-Deterministic AI Agent Workflows
cs.AIcs.SE
→ Stochastic testing across non-deterministic agent workflows
Read on arXiv →arXiv:2604.06392
Qualixar OS: A Universal Agent Operating System
cs.AI
→ Universal Type-C port for AI agents — 25 commands, every transport, every IDE
Read on arXiv →Experience
Career & Expertise
Accenture
Senior Manager & Solution Architect
RetailEnergyAviationTelecomChemicals
Leading digital transformation programs for Fortune 500 European enterprises. Managing 100+ member teams across multiple concurrent projects. End-to-end solutioning with GenAI and Agentic AI.
5× Global Technology Innovation Award Winner (2021–2025). Built AI platforms for automated voice dubbing, sound effects generation, and video production — recognized in national media.
Tech Mahindra
Software Engineer
US TelecomBanking
Enterprise solution development for major US telecom and banking institutions.
HCL Technologies
Software Engineer
Retail/QSRTelecom
Digital platform development for global retail and telecom enterprises.
Alcatel-Lucent
Network Engineer
NetworkingTelecom
Where the journey began — building networking infrastructure for telecom carriers.
Technical Expertise
Tools & Technologies
Cloud & Infrastructure
AzureGCPAWS
Digital Experience
Adobe AEMTargetCampaignFirefly
Commerce
HCL CommerceSAP Hybris
Backend
JavaSpring BootMicroservices
Frontend
Next.jsNode.jsReact
AI & ML
PythonNLPLLM DevelopmentGenAIAgentic AI
Architecture
Solution DesignDigital TransformationFull SDLC
Education
Dual Degree: B.Tech (Engineering) + LLB (Law)
The Bridge
Sāṅkhya described multi-agent systems three thousand years ago.
Daily study of Advaita Vedanta with Shankara’s commentaries. The tradition’s emphasis on pramāṇa — valid means of knowledge — directly informs the formal verification methodology used across Qualixar instruments. Vedanta is the original reliability engineering: a method for testing the mind’s outputs against an unchanging reference.
“Pramāṇe ādhīnā prameya-siddhiḥ.”The valid object stands on the valid means of knowledge. — Nyāya
Tractable in code: every agent assertion is a prameya; every contract, regression, and supply-chain check is a pramāṇa; every production failure is a doṣadṛṣṭi — the cataloged flaw of perception that the system must be tuned away from.
Read the full essayWriting
From the build log.
The Digital Tantra: Prakāśa and Vimarśa in the Agentic AI Stack
How the Kashmir Shaivism concepts of Prakāśa (luminous awareness) and Vimarśa (active self-reflection) map to the transition from static LLM weights to dynamic agentic loops.
Pramāṇa for AI Agents: Indian Epistemology as the Original Reliability Engineering
How classical Indian validation systems (pramāṇa-vāda) map to modern software engineering for non-deterministic AI agent systems.
Google Just Validated What We Built: Why Jitro Proves AI Agents Need Persistent Memory
Google's Project Jitro (Jules V2) is building a persistent agentic workspace with goals, insights, and history. This is exactly the problem SuperLocalMemory solved — locally, privately, and months earlier.
"The signal is always there.
You just have to build the filter."
7 live instruments in the Qualixar suite. New research every few weeks.
Follow the build.