MAYANK GOYAL

About Me

I build software to solve specific, practical problems. No fluff, no corporate buzzwords—just clean layouts and tools designed to do exactly what they were built to do.

I don't care about surface-level professional titles. I prefer to let the work speak for itself, focusing my energy on functional categories like client-side architecture and building tangible systems from the ground up. If you want to know what I am capable of, look at the codebase, not a label.

I have a strong preference for local development and data privacy. Whenever possible, I choose to spin up lightweight local setups—like running Mistral via Ollama—to avoid unnecessary subscription costs and keep data completely secure and self-contained.

Clean folder structures and tight, modular layouts aren't an afterthought for me; they are foundational to a stable project. I spend the extra time making sure a repository is organized logically so it can be maintained, scaled, and understood immediately by other developers.

I build things that address real, day-to-day operational friction—whether that means connecting git commits to tracking tickets or automating messy proof-of-delivery paperwork for logistics. If a tool doesn't make a concrete process more efficient, it's just noise.

My approach is straightforward: clear goals, direct communication, and spending less time debating theories and more time handling edge cases. I don't treat system constraints or bugs like a crisis; they are just puzzles to be systematically broken down and cleared.

A portfolio shouldn't be an exercise in creative writing. Every project featured here was built to work reliably in the real world. If you appreciate straightforward engineering without the corporate theater, you'll navigate through my work just fine.

Developer Workbench

Operational capabilities, applied mechanics, and data flow systems.

Local Intelligence & Language Models

Local Architecture

Local RAG engine deployment connecting version control data directly to project management systems.

Model Orchestration

Custom local pipeline integration utilizing Mistral via Ollama to ensure complete data privacy.

Core Toolkit
PyTorch TensorFlow MediaPipe LSTM
Explore Research Labs

Data Architecture & Automation

Automated Ingestion

Custom ingestion processing utilizing fuzzy matching and relational cloud schemas to automate document pipelines.

Signal & Spatial Processing

Spatio-Temporal Graph Neural Networks and 1D-CNN model architecture for complex signal processing.

Core Toolkit
Python Pandas Scikit-learn Supabase Advanced SQL
Explore Research Labs

Backends & Deployment Interfaces

API Development

High-performance asynchronous backends engineered for real-time inference delivery.

Modular Engineering

Strict object-oriented design patterns with clean, highly modular file structures.

Core Toolkit
FastAPI Streamlit Git Architecture
Explore Research Labs

> CORE APPLIED TECH STACK MATRIX

Domain Core Ecosystem Applied Mechanics
Intelligent Systems Python, Ollama, Mistral, Supabase Local RAG, Custom Vector Ingestion, Sequence Processing
Data Engineering Pandas, Scikit-learn, SQL, TensorFlow Spatio-Temporal Modeling, 1D-CNN Signal Processing
Service Backends FastAPI, Streamlit, REST APIs Asynchronous Frameworks, Modular Architecture

Featured Showcase

Mission logs from shipped experiments and interfaces.

Explore my comprehensive project collections across different domains:

01. Data & Analytics

Custom ingestion processing, relational schemas, and handling fuzzy-matching pipelines.

Explore Analytics →

02. Python Backends

Modular script architecture, strict object-oriented structures, and clean codebase layouts.

Explore Python →

03. Machine Learning

Practical, deployable pipelines engineered for direct model execution and testing.

Explore ML →

04. Deep Learning & Signals

Spatio-temporal network routing and 1D-CNN implementations for complex signal arrays.

Explore DL →
> curl -s api/

05. FastAPI Engines

Asynchronous service architecture designed for fast execution and real-time backend delivery.

Explore FastAPI →

06. Generative AI

Local LLM pipeline orchestration and custom RAG engines focused on strict data privacy.

Explore GenAI →

07. Natural Language Processing

Complex sequence modeling, token tracking, and semantic translation setups.

Explore NLP →
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Open Channel

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I usually respond within 24 hours to collaboration ideas, data projects, or research opportunities.