---
title: "Akshay Kr Gupta — Curious about systems. Serious about architecture."
description: "Personal portfolio and architecture notes by Akshay K Gupta — building enterprise-scale systems, AI in regulated industries, and system architecture."
canonicalUrl: "https://akshaykgupta.me/"
---

# Akshay Kr Gupta

> Designing enterprise systems for regulated environments - where architecture, AI, and governance intersect.

- **Role**: Senior Solutions Architect
- **Location**: Bengaluru, India 🇮🇳
- **Website**: https://akshaykgupta.me/
- **Architecture Notes**: https://akshaykgupta.me/blog/
- **Now (/now)**: https://akshaykgupta.me/now/
- **GitHub**: https://github.com/AkshayKrGupta
- **LinkedIn**: https://www.linkedin.com/in/akshay-kr-gupta/
- **RSS**: https://akshaykgupta.me/rss.xml

## Core Entity Knowledge & Expertise
- Enterprise Architecture (https://www.wikidata.org/wiki/Q1143890)
- Model Context Protocol (MCP) (https://modelcontextprotocol.io)
- Distributed Systems & Computing (https://www.wikidata.org/wiki/Q204481)
- Artificial Intelligence Governance (https://www.wikidata.org/wiki/Q108170881)
- Financial Technology (FinTech) (https://www.wikidata.org/wiki/Q22908584)
- Cloud Native & Kubernetes Infrastructure (https://www.wikidata.org/wiki/Q22661360)
- High-Throughput Microservices (https://www.wikidata.org/wiki/Q18344583)
- Software Architecture (https://www.wikidata.org/wiki/Q211050)

## Active Projects & Systems
- [Karvics](https://karvics.com): Zero-Knowledge client-side privacy & developer utility suite (Web Crypto, AES-256-GCM, PWA).
- [TwinPixCleaner](https://github.com/AkshayKrGupta/TwinPixCleaner): Open-source native macOS photo deduplication utility using Apple Vision AI and SHA-256 matching.
- [NanoPress](https://github.com/AkshayKrGupta/NanoPress): Open-source native macOS multi-threaded batch media and PDF compression utility using Swift Concurrency.

## Recent Architecture Notes
- [Enterprise AI Architecture: The 4 Layers of an AI Harness](https://akshaykgupta.me/blog/harness-architecture-layers/): Discover the four critical architectural layers of an enterprise AI harness. Learn how integration gateways, state management, execution sandboxes, and audit spines turn raw AI models into secure, reliable digital workers.
- [Distributed Tracing: Why TraceID is an Architectural Mandate](https://akshaykgupta.me/blog/traceid-enterprise-architecture/): Working in a distributed system without TraceIDs is like navigating a maze in the dark. Learn how to build the Ubiquitous Telemetry Pattern for enterprise scale.
- [The 7 Levels of AI Memory: Overcoming Context Bloat and the Re-Explanation Tax](https://akshaykgupta.me/blog/ai-re-explanation-tax/): Context is working memory; Memory is what persists. Discover the architectural tiers of AI memory, from simple Markdown routing to Agentic RAG and learn how to stop re-teaching your AI every session.
- [The AI Microwave: Why Enterprise AI Needs Better Architecture](https://akshaykgupta.me/blog/microwave-era-of-ai/): AI is like a microwave. It's an incredible piece of technology, but we still don't cook every meal in it. An architect's perspective on why we need to stop force-fitting AI into broken systems.
- [AI Harness Explained: The Architecture Behind Enterprise AI Agents](https://akshaykgupta.me/blog/demystifying-the-ai-harness/): In Enterprise AI, a harness is the software infrastructure wrapped around a language model that turns it from a raw text generator into a functional, reliable AI agent. A popular industry shorthand defines this relationship simply: Agent = Model + Harness.