01
Research
Understanding the goal, requirements, and technical challenges to build a plan.

Engineering autonomous AIOps incident engines, enterprise RAG architectures, MCP protocol servers, multi-agent debate arenas, and custom transformers from first principles. Specializing in Python, FastAPI, and React.js.
Belagavi, Karnataka
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Open for AI / ML Roles
Full-Time / Remote / Onsite
B.E. AI & ML
Jain College of Engineering
5+ Models Unified
REST & WebSocket APIs

Kartik Raikar
AI Systems • LLM Evaluation • Transformers
Hello! I'm Kartik
I am an AI & Machine Learning Engineer passionate about architecting high-performance AIOps incident engines, enterprise RAG architectures, MCP protocol servers, multi-agent debate arenas, and neural transformers built from mathematical first principles.
Currently pursuing B.E. in Artificial Intelligence & Machine Learning at VTU with an 8.5 CGPA and serving as Vice President of the AIML Department at Jain College of Engineering. Competitor in national hackathons including IIIT Dharwad Hack2Future 2.0 (Team VELORA) and NITTE Code for Innovex.
10
Flagship AI Systems
5
LLMs Orchestrated
8.5
CGPA (AI & ML @ VTU)
100%
From Scratch Transformer
Categorized by engineering tier and real-world system implementations. No arbitrary percentage bars — each competency is backed by production repositories and benchmarks.
RAG Evaluation • Agents • Neural Internals
Manual 8-head attention, backprop & causal masking
Version-partitioned vector indexing & AST semantic diffs
Multi-turn debate state machines & LLM persona synthesis
Cross-encoder re-ranking & Reciprocal Rank Fusion (k=60)
Two-phase SHA256 tokens & Saga transaction rollbacks
High-Throughput Services • Async Sockets
Primary daily language for all microservices & agents
Strict schema contracts, streaming SSE & dependency injection
Sub-45ms real-time telemetry streaming & socket multiplexing
Full-stack UI with TanStack Start, Tailwind v4 & Vite
NetworkX graph algorithms & EWMA anomaly isolation
Hybrid Search • Vector Indices • Graphs
HNSW index partitioning & 5.4ms cosine similarity lookup
Embedded vector stores & collection filtering on CPU
In-memory caching, pub/sub messaging & rate-limiting
Document storage & knowledge graph lineage modeling
Containerization • Observability • CI/CD
Multi-stage builds, isolated runtime sandboxes & compose
Automated test suites, linter gates & semantic releases
Zero-cost local LLM inference (Llama 3.1, Phi-3, Mistral)
Process orchestration, systemd management & shell tooling
Real-time 3D topology graphs & simulation rendering
I follow a structured, creative, and highly technical approach to turn ideas into robust full-stack applications.
01
Understanding the goal, requirements, and technical challenges to build a plan.
02
Creating clean interfaces, intuitive experiences and scalable user journeys.
03
Developing fast, reliable and maintainable full-stack applications.
04
Shipping to production, monitoring performance and iterating on feedback.
A selection of 10 production-grade AI systems, LLM evaluation pipelines, RAG benchmarking harnesses, MCP servers, and zero-framework transformers architected by Kartik Raikar. Click tabs on any project to explore metrics, challenges, solutions, and interview deep dives.
AIOps Incident Intelligence
// SYSTEM #01 OF 10Autonomous Incident Correlation Engine for Microservice Alert Storms
An autonomous incident correlation engine that resolves cascading microservice alert storms in 0.78s (down from 1–4 hours of manual tracing), achieving 100% Top-1 RCA accuracy across 30 benchmark scenarios. Features dynamic EWMA anomaly detection with causal DAG traversal and a real-time 3D topology telemetry visualizer.
0.78s
Resolution Time
Down from 1–4 hours manual
100%
Top-1 RCA Accuracy
30 benchmark scenarios
z > 2.0σ
EWMA Detection
Dynamic anomaly threshold
3D WebGL
Topology Visualizer
Three.js + WebSockets
Key Quantitative Highlights:
Documentation Intelligence Engine
// SYSTEM #02 OF 10Enterprise RAG Architecture Resolving Cross-Version Code Contamination
An enterprise RAG architecture that resolves cross-version code contamination, eliminating hallucinated deprecated API calls from 62.5% to 0.0% via database-enforced version-partitioned vector indexing. Features a structure-aware AST semantic diff engine and a 4-step Chain-of-Version reasoning pipeline.
0.0%
API Contamination
Down from 62.5% hallucination
98.4%
Precision @ k=6
Up from 41.7% (+136%)
94.2%
AST Diff Accuracy
Undocumented breaking changes
5.4ms
HNSW Latency
pgvector indexed search
Key Quantitative Highlights:
Model Context Protocol & Saga Engine
// SYSTEM #03 OF 10Enterprise Model Context Protocol (MCP) Server with Two-Phase Auth & Saga Rollbacks
Production-grade Model Context Protocol (MCP) server exposing 12+ tools for autonomous LLM GitHub repository management. Features a two-phase preview-token confirmation flow for bulk actions, a file-backed Saga transaction journal for atomic rollbacks, a pure-Python TF-IDF vector engine, and a declarative ABAC policy engine.
62% → 98%
Tool Selection Accuracy
Evaluated across 50 benchmark queries (+36% gain)
0%
Blind Bulk Mutations
Eliminated 100% of unverified writes (-14% baseline)
86% → 100%
Local LLM Usable Output
Defensive JSON parser recovery (llama3.2:1b)
12 Tools
Executable MCP Schema
Saga Pattern append-only compensation journal
Key Quantitative Highlights:
Production RAG Benchmarking Harness
// SYSTEM #04 OF 10Production-Grade RAG Evaluation & 5-Strategy Benchmarking Harness ($0 Cost)
A research-grade RAG evaluation harness benchmarking 5 retrieval strategies (Simple BM25, Semantic Vector, Hybrid RRF, Cross-Encoder Rerank, and Learned ML Router) across 100 human-verified Q&A pairs on React documentation — operating entirely on local CPU hardware at $0 marginal infrastructure cost.
61% → 85%
Recall@4 Accuracy
Cross-Encoder Re-Ranker (+24% gain)
$0.00
Marginal Cost
100% Local CPU & ChromaDB
2,580
Corpus Chunks
React v17 (716) & react.dev (1,864)
100 Pairs
Human Q&A Eval
0% synthetic data in eval set
Key Quantitative Highlights:
Flagship Production RAG System
// SYSTEM #05 OF 10"Talk with my Resume." — Full-Stack AI Career Portal & RAG Studio
A production-quality, full-stack AI Resume Portal engineered with futuristic dark glassmorphic aesthetics and smooth micro-interactions. Enables recruiters to explore credentials interactively, inspect a high-fidelity PDF layout with real-time keyword highlights, and converse with Atlas AI—an intelligent agent powered by Gemini 3.5 Flash, dynamic vector embeddings, Dual-Engine retrieval, and Server-Sent Events (SSE) word-by-word streaming.
< 18ms
SSE Stream Latency
Word-by-word token delivery
0ms
PDF Layout Shift
Canvas text highlight sync
1,864
Document Chunks
Gemini Embedding 2 Preview
Dual Engine
Vector + Keyword
Cosine similarity + BM25
Key Quantitative Highlights:
Autonomous AI Operating System
// SYSTEM #06 OF 10Next-Gen Web-Based AI Desktop Environment & Multi-Agent OS
A futuristic web-based AI operating system and intelligent workspace. Features windowed multi-tasking, integrated virtual web terminal, file system sandbox, autonomous agent co-pilots, and dynamic system telemetry built with React 19, TypeScript, and FastAPI.
60 FPS
Frame Rate Physics
Zero layout-thrashing UI
< 15ms
IPC Sync Latency
Web Worker virtual process bus
100%
Sandbox Isolation
Virtual FS security boundary
4 Co-Pilots
Autonomous Agents
Concurrent terminal execution
Key Quantitative Highlights:
Multi-Agent Orchestration
// SYSTEM #07 OF 10Autonomous Multi-Model Debate & Courtroom Visualizer
An AI-powered multi-agent debate platform with real-time argument generation and interactive courtroom visualization. Integrated language model APIs (Gemini, GPT-4, Claude) for intelligent persona synthesis and counter-argumentation. Designed a responsive courtroom frontend in React and TailwindCSS with FastAPI backend and live WebSocket streaming.
3 Agents
Debate Personas
Gemini, GPT-4o & Claude 3.5 Sonnet
< 30ms
Sentiment Overlay
Continuous stance & tone scoring
100%
State Synchronization
Live WebSocket courtroom sync
3-Tier
Judge Scoring Rubric
Automated argument evaluation
Key Quantitative Highlights:
Enterprise LLM Evaluation
// SYSTEM #08 OF 10Full-Stack Enterprise LLM Evaluation & Benchmarking Platform
Architected a full-stack platform scoring LLM outputs across faithfulness, relevance, toxicity, and correctness. Integrated five LLM providers (GPT-4, Claude 3.5, Gemini, Llama 3, Mistral) behind a unified REST API with WebSocket streaming for real-time benchmark telemetry and automated regression testing.
99.4%
Scoring Accuracy
Across 4 evaluation dimensions
5 LLMs
Orchestrated Providers
GPT-4, Claude, Gemini, Llama, Mistral
< 45ms
WebSocket Telemetry
Real-time benchmark streaming
100%
Toxicity Audit Rate
Automated regression testing
Key Quantitative Highlights:
Deep Learning Internals
// SYSTEM #09 OF 10Zero-Framework GPT Transformer Built from Mathematical First Principles
A complete GPT-style Transformer model implemented completely from scratch without external ML frameworks (no PyTorch, no TensorFlow). Manually engineered Matrix Multiplication, 8-Head Multi-Head Attention, Layer Normalization, Softmax, FeedForward layers, and Backpropagation. Includes an interactive visualizer for live activation matrices and attention heatmaps.
0%
ML Frameworks
0 PyTorch, 0 TensorFlow
8 Heads
Multi-Head Attention
Manual Causal Masking
384-dim
Vector Embedding
Analytical backpropagation gradients
100%
Pure Matrix Math
Manual Softmax & LayerNorm
Key Quantitative Highlights:
Frontend Engineering
// SYSTEM #10 OF 10Modern Interactive Calculator with Clean UI & Keyboard Support
A beautifully designed, fully functional calculator application built with modern web technologies. Features clean UI design, keyboard shortcut support, calculation history, and responsive layout optimized for all devices.
100%
Keyboard Support
Full numpad & operators
60 FPS
UI Animations
Smooth button interactions
0 Deps
External Libraries
Pure vanilla implementation
Responsive
Cross-Device
Mobile-first design
Key Quantitative Highlights:
Department executive leadership as AIML Vice President and national hackathon competitor across leading technical institutes of India.
Jain College of Engineering, Belagavi
Elected as Vice President of the AI & Machine Learning Department. Spearheading departmental technical initiatives, leading student hackathons, organizing national workshops, and coordinating academic & technical programs for the entire department.
Key Highlights
VP
Role
AI & ML
Department
Academic
Scope
Indian Institute of Information Technology, Dharwad
Certificate of Participation — National-Level Hackathon organized by IIIT Dharwad, IIC, IDRP, Infosys Research Park & Devfolio. Competed as part of Team VELORA, building AI/ML prototypes under intense time constraints.
Key Highlights
VELORA
Team
National
Format
IIITD
Host
NMAM Institute of Technology, Mangalore
Certificate of Appreciation — 24-Hour National-Level Hackathon organized by the NSS IT Wing at NMAM Institute of Technology (NITTE University). Architected and presented full-stack solutions to university & industry judges.
Key Highlights
24 Hrs
Duration
National
Level
Cert.
Award
A verified record of 23 specialized certifications spanning Oracle Generative AI & Agentic AI, Apache Kafka, AWS Machine Learning, Cisco Cybersecurity, and enterprise data analytics simulations.
Issued Oct 2026

Mastery of Apache Kafka distributed architecture, high-throughput event streaming, message partitioning, consumer groups, and building fault-tolerant scalable backends.
Issued Jul 2026

Demonstrates foundational knowledge of artificial intelligence, machine learning, Generative AI, Large Language Models (LLMs), and Oracle Cloud Infrastructure AI services.
Issued Jul 2026

Demonstrates foundational knowledge of Agentic AI, including autonomous AI agents, agent architectures, task execution pipelines, tool use, reasoning, and orchestration.
Issued Oct 2025

Demonstrates professional-level knowledge of AI Vector Search, vector indexes, similarity distance metrics, semantic search, and enterprise RAG architecture.
Issued Sep 2025

Demonstrates professional-level knowledge of Generative AI concepts, LLM fine-tuning, retrieval architectures, and deploying production model pipelines on OCI.
Issued Sep 2025

Comprehensive certification verifying mastery of OCI Artificial Intelligence architectures, generative models, and machine learning foundation concepts.
Issued Sep 2026

Certificate recognizing active membership and contributions in Artificial Intelligence initiatives, workshops, and project collaborations at SPARK IIT during 2026.
Issued Sep 2026

Certificate documenting successful completion of a rigorous 90-day Artificial Intelligence training program at SPARK IIT, completed from July to September 2026.
Issued Sep 2026

Internship Completion Certificate for successfully completing a Machine Learning Internship at Cognifyz IT Solutions Pvt. Ltd., developing and validating production ML algorithms.
Issued Aug 2026

Certificate of Completion awarded by GUVI for successfully completing the Claude AI in 90 Minutes course, demonstrating practical prompt architecture and workflow automation.
Issued Jul 2026

Successfully completed Deloitte's Data Analytics Job Simulation on Forage, gaining hands-on experience in data analysis, forensic technology, and executive insight reporting.
Issued Jun 2026

Comprehensive certification covering business communication, presentation, IT methodologies, collaborative workflows, and corporate development frameworks.
Issued Jun 2026

Completed AWS Skill Builder specialized curriculum on core AI algorithms, neural network design, model training, and generative AI deployments on AWS.
Issued Jun 2026

Gained foundational knowledge of cybersecurity, online threats, digital security, network defense, cryptographic safeguards, and information protection through Cisco.
Issued Jun 2026

Completed a practical data analytics simulation focused on data cleaning, dashboard development, data visualization, business insights generation, and executive metrics.
Issued Jun 2026

Completed a cybersecurity simulation focused on Identity and Access Management (IAM), cybersecurity best practices, IAM assessments, and security solution design.
Issued Jun 2026

Completed Tata's GenAI Powered Data Analytics Job Simulation on Forage, developing hands-on experience in leveraging Generative AI for exploratory data analytics.
Issued Sep 2025

Certificate of Completion awarded by IBM Training on September 1, 2025, for hands-on proficiency in process mining, algorithmic bottleneck detection, and workflow transformation.
Issued Aug 2025

Engineered an end-to-end full stack web application featuring responsive customer UI, authentication, database schemas, admin dashboard, and payment gateway.
Issued Aug 2025

Microsoft verified credential for cloud computing fundamentals, compute virtualization, storage topologies, and Azure governance frameworks.
Issued Aug 2026

Completed Skyscanner's official front-end engineering job simulation on Forage, building real-world UI components and applying industry-standard React development practices.
Issued Jul 2026

Completed Walnut's sales technology job simulation on Forage, optimizing interactive SaaS product tours, analytics conversion funnels, and enterprise workflows.
Issued Aug 2026

Certificate of Completion awarded by IEEE Blended Learning Program for mastering Introduction to IoT principles, connected sensor network architectures, and smart device communication frameworks.
Have an AI engineering role, collaborative project, or an idea in mind? Reach out directly via Gmail, phone, or connect across professional networks.
Email Address
kartikraikar2005@gmail.com
GitHub Codebase
@kartik-012
LinkedIn Network
@kartik-raikar-kr
© 2026 Kartik Raikar — AI Engineer & Systems Architect
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