# Ajay Kumar Sharma — Full Portfolio Content for AI Agents > This is the extended machine-readable content file for AI agents. > For a summary, see: https://www.ajaykumarsharma.co.in/llms.txt > Last updated: 2026-09 --- ## IDENTITY Name: Ajay Kumar Sharma Location: Jaipur, Rajasthan, India (works worldwide and remote) Email: ajaysharmabki96@gmail.com Website: https://www.ajaykumarsharma.co.in Link hub: https://links.ajaykumarsharma.co.in (every channel in one place, plus the free AI Agent Architecture course). Its own machine-readable files are at /llms.txt and /llms-full.txt on that domain. YouTube: https://www.youtube.com/@ajaysharmaAI - the free AI Agent Architecture course: eight parts, no sign-up, nothing to buy. Same architecture used on paid client work. Instagram: https://www.instagram.com/ajaysharma_ai Roles: AI Engineer, Software Engineer, Entrepreneur Bio: Ajay is an AI Engineer who builds AI products, agents, custom software, and web apps end to end - from idea to production. Bring an idea or a stuck project; he designs the architecture, chooses the right stack, and ships it live. Enterprise RAG and knowledge systems are his flagship specialty - production retrieval with citation-backed answers, hybrid search, and no hallucinations - but he is stack-agnostic and delivers the complete product, not just the AI core. Core stack: LangGraph, Pinecone, FastAPI, Next.js, AWS. --- ## WHAT I BUILD (capabilities) 1. Enterprise RAG & Knowledge Systems (FLAGSHIP) - Production retrieval over sprawling documentation with citations and no hallucinations. URL: /services/enterprise-rag 2. AI Agent Development - Custom AI agents and multi-agent systems that plan, retrieve, reason, and act - not single-shot prompts. URL: /services/ai-agents 3. AI Automation - Automation and integrations that connect your tools and remove manual busywork. URL: /services/ai-automation 4. AI Product & SaaS Development - Your idea taken from concept to a live, shipped product: the AI core and the app around it. URL: /services/ai-product-development 5. Custom Software & Web Apps - Full-stack software and web applications, designed and built end to end. Any stack. URL: /services/custom-software 6. AI Consulting & Fractional - Architecture reviews, AI integration, and fractional AI architecture for teams building with AI. URL: /services/ai-consulting --- ## COMPANIES ### NirixAI - Role: Founder, CEO, CTO - Type: AI Engineering practice / agency - Focus: Production AI agents, AI SaaS products, custom software, web apps, and AI consulting - Flagship Product: NirixAI Learning Assistant - YouTube video interaction, automatic summaries, quizzes from video, document interaction ### Tim Edge - Role: Co-Founder, CTO - Type: Trading technology platform (timedge.in) ### Tim Academy - Type: Online trading education platform - "The Mechanical Trading Lab" (timacademy.in) - Offerings: Proprietary trading frameworks, live Trading Arena, monthly Execution Labs, performance-based credential - Goal: Teach systematic, rule-based trading instead of emotional decision-making --- ## TECH STACK Programming Languages: Python, JavaScript, TypeScript, SQL Frontend: React.js, Next.js, TailwindCSS Backend: FastAPI, Django, Flask AI/LLM Frameworks: LangGraph, LangChain LLMs: Multi-LLM routing (OpenAI, Anthropic Claude) Vector Databases: Pinecone Databases: PostgreSQL (Supabase) Cloud: AWS (production + staging) Stack-agnostic: tools are chosen to fit the problem, not a fixed toolkit. --- ## AI ENGINEERING PHILOSOPHY Architecture-first approach: - Modular AI systems over monolithic prompts - Scalable, production-ready infrastructure - Multi-agent orchestration patterns - Systems architecture thinking over one-off prompting --- ## CASE STUDIES (DETAILED) ### 1. NirixAI — AI Learning Assistant + Production RAG - Website: https://nirixai.com/ - Status: PRODUCTION - Description: AI learning assistant that turns videos and documents into summaries, quizzes, and cited Q&A with real-time streaming responses. Built on Pinecone with hybrid search, multi-LLM routing, and SSE streaming - the full ingestion -> embedding -> retrieval -> generation pipeline applied to messy, multi-format content at interactive latency. - Outcome: Serves streaming answers from a 20K+ content corpus with sub-2-second first-token latency. - Tech: LangGraph RAG, Hybrid Search, Pinecone, Multi-LLM Routing, SSE Streaming ### 2. PiperQL — Natural-Language Database Agent - Website: https://piperql.vercel.app - GitHub: https://github.com/ajaysharmadeveloper/piperql - Status: PRODUCTION (open source, AGPL v3) - Description: Natural-language database agent that lets non-technical teams (ops, finance, HR) self-serve complex database queries without writing SQL. Handles multi-turn conversation context, auto-generates visualizations, and runs in three deployment modes. - Outcome: Open-sourced under AGPL v3. Architecture scales to enterprise-grade query workloads. - Tech: LangGraph + OpenAI, Natural Language to SQL, Auto-Generated Charts, Mem0 AI Memory ### 3. Tim Edge — High-Concurrency Trading Platform - Website: https://timedge.in - Status: PRODUCTION - Description: Full-stack trading platform with live market data streaming, automated trade logic, journaling, and backtesting. Architected with MetaAPI integration, WebSocket streaming, Celery async workers, and AWS infrastructure - high-concurrency, low-latency system design, the same patterns required for real-time enterprise retrieval. - Tech: MetaAPI + Fyers Integration, WebSocket, Celery Multi-Worker Architecture, AWS ### 4. Tim Academy — End-to-End Education Platform - Website: https://timacademy.in/ - Status: PRODUCTION - Description: Full-stack education platform with live streaming (100ms), authentication, payments, and structured learning paths. End-to-end product delivery - design, implementation, infrastructure, and launch. - Tech: Live Streaming (100ms), Payments, Auth ### Earlier AI engineering work (client projects) Production RAG and AI assistant systems built for international brands, demonstrating enterprise retrieval experience: - Multilingual product-recommendation assistant for a coffee brand (product info, compatibility detection) - Hair-care recommendation assistant (product suggestions, appointment booking, FAQ handling) - Fine-tuned assistant for a ship-modeling product catalog - Multi-index vector search across multiple Pinecone indexes with a universal metadata parser - Enterprise RAG pipelines with hybrid search, optimized embeddings, and metadata-driven retrieval --- ## WAYS TO WORK TOGETHER Pricing is not public - it is scoped on a 60-minute strategy call based on goals, document volume, compliance posture, and integration complexity. Start with a Custom Build scoped to your idea, or pick a fixed-scope Enterprise RAG package. ### Custom Build (START HERE) - Duration: scoped on the call - Ideal for: AI agents, AI SaaS, custom software & web apps - any stack - Deliverables: architecture and build plan mapped end to end; full-stack delivery (AI, backend, web app, interface); shipped to production, not a demo; right tools chosen to fit the problem; clear scope and a fixed quote before any build starts - CTA: /book?package=custom ### RAG Readiness Audit - Duration: 2 weeks - Ideal for: first engagement, low commitment; converts to pilot in ~60% of cases - Deliverables: content inventory & classification, top 3 ROI use cases, data security & compliance assessment, phased architecture recommendation, 25-page report + 60-min walkthrough - CTA: /book?package=audit ### RAG Pilot Build - Duration: 6-8 weeks - Ideal for: teams ready to commit to one clear use case, up to ~10,000 documents - Deliverables: hybrid retrieval (BM25 + vector) with reranking, inline citations, basic UI or Slack/Teams integration, cloud deployment with monitoring + logging, 2 weeks post-launch support - CTA: /book?package=pilot ### Enterprise RAG Platform - Duration: 3-4 months - Ideal for: organizations standardizing on an internal knowledge platform - Deliverables: multi-source ingestion (SharePoint, Confluence, Google Drive, S3, databases), RBAC + audit logs, metadata filtering and permission-aware retrieval, agents for multi-step retrieval, evaluation harness + monitoring dashboards, feedback loop, 3-5 custom integrations, team handover training - CTA: /book?package=platform ### Fractional AI Architect - Duration: 2 days/week, 3-month minimum - Ideal for: in-house teams that need senior architectural guidance without a full-time hire - Deliverables: weekly architecture reviews, hands-on implementation guidance, code review & PR feedback, team upskilling, direct Slack access during engagement days - CTA: /book?package=fractional --- ## ENGAGEMENT STANDARDS 1. Architecture-first over prompt hacking 2. Hybrid retrieval (BM25 + vector + reranking), never pure vector 3. Citations on every answer; "I don't know" is a valid response 4. Production infrastructure (monitoring, logging, alerting, runbooks), not notebooks 5. Client data stays in the client's cloud - self-hosted, zero-retention API, or hybrid 6. Handover, not dependency - client teams own the system at the end --- ## BLOG (35+ posts — full list at /feed.xml and /sitemap.xml) Recent and representative posts: - Why Your AI Agent Works in Demos but Fails in Production - 5 Real Fixes (2026-07-11) - /blog/why-your-ai-agent-works-in-demos-but-fails-in-prod - Embracing the Future of Document Processing with DocLing (2026-07-06) - /blog/embracing-the-future-of-document-processing-with-d - Why the Industrial Data Problem is Crippling AI Adoption (2026-05-13) - /blog/why-the-industrial-data-problem-is-crippling-ai-ad - AI Agents: Transforming Hotel Operations from the Ground Up (2026-04-13) - /blog/ai-agents-transforming-hotel-operations-from-the-g - AI's Real Value in Business - A Practical Guide (2026-04-07) - /blog/ai-s-real-value-beyond-the-hype-a-practical-guide - Why Agentic AI Needs Boundaries Before Freedom (2026-04-04) - /blog/why-agentic-ai-needs-boundaries-before-freedom - Moving from Code Reviewer to Architect in an AI-Saturated Workflow (2026-04-02) - /blog/moving-from-code-reviewer-to-architect-in-an-ai-sa - OpenClaw vs LangGraph: Comparing AI Agent Architectures for Production (2026-03-22) - /blog/openclaw-vs-langgraph-comparing-ai-agent-architect - Why Trust - Not Discovery - Is the Real Infrastructure Problem for AI Agents (2026-03-18) - /blog/agent-trust-infrastructure - Claude Code's Four Layers: Agents, Skills, Hooks, and Memory (2026-03-15) - /blog/claude-code-agents-skills-hooks-memory - Why Multi-Agent Architecture Beats Single-Agent LLM Wrappers (2026-03-09) - /blog/why-multi-agent-architecture - Building RAG That Actually Works: Lessons From 5 Production Systems (2026-03-02) - /blog/building-rag-that-works - The Architecture-First Approach to AI Engineering (2026-02-23) - /blog/architecture-first-ai-engineering Themes: AI agents in production (reliability, failure patterns, governance), enterprise RAG, hybrid search vs pure vector, LangGraph multi-agent orchestration, architecture-first AI engineering, Claude Code developer productivity, document processing, and AI industry analysis. --- ## SITE PAGES - Home: https://www.ajaykumarsharma.co.in/ - Case Studies / Projects: https://www.ajaykumarsharma.co.in/projects - Services (all capabilities + packages): https://www.ajaykumarsharma.co.in/services - Enterprise RAG: /services/enterprise-rag - AI Agents: /services/ai-agents - AI Automation: /services/ai-automation - AI Product & SaaS Development: /services/ai-product-development - Custom Software & Web Apps: /services/custom-software - AI Consulting & Fractional: /services/ai-consulting - Blog: https://www.ajaykumarsharma.co.in/blog - Book a Strategy Call: https://www.ajaykumarsharma.co.in/book - Book a specific package: /book?package=custom | audit | pilot | platform | fractional - Contact: https://www.ajaykumarsharma.co.in/contact --- ## CONTACT Email: ajaysharmabki96@gmail.com Contact form: https://www.ajaykumarsharma.co.in/contact Booking: https://www.ajaykumarsharma.co.in/book Status: Online — Accepting new engagements