Full-stack software, websites, AI, and automation built beautifully.

Problem

Sales teams lose pipeline time on outdated data, low-fit prospects, and manual follow-ups.

Does

Finds verified buyers, scores intent, supports AI SDR outreach, and moves qualified accounts toward meetings.

Outcome

Reduced prospecting friction and made outreach feel more targeted, timely, and measurable.

Problem

Product, marketing, and success teams spend days recreating demos, launch videos, and help content.

Does

Repurposes product recordings into demos, guides, videos, support assets, and analytics-backed content.

Outcome

Helped teams ship product stories faster and reuse content across sales, onboarding, and education.

Problem

Teams need product demos and training content quickly, but manual recording, editing, and documentation slows launches.

Does

Converts recordings into interactive demos, step guides, captions, extension flows, and AI voiceover assets.

Outcome

Shortened demo production cycles and made product education easier to reuse across channels.

Problem

Product data teams need accurate, validated, and centralized records across complex catalog workflows.

Does

Manages product data through scalable Go services, MongoDB storage, REST APIs, validations, and integrations.

Outcome

Improved product-data reliability and created a stronger foundation for enterprise catalog operations.

Problem

Engineering teams repeat setup work across APIs, CI/CD, Docker, infrastructure, and project boilerplate.

Does

Generates backend structures, deployment files, pipelines, and starter code from guided LLM workflows.

Outcome

Reduced repetitive setup time and gave developers a faster path from idea to working project structure.

Problem

Real-estate buyers and sellers need trusted listings, project discovery, location context, and secure browsing flows.

Does

Presents property listings, discovery pages, content updates, and user-friendly browsing across responsive interfaces.

Outcome

Created a clearer real-estate discovery experience for customers comparing properties and market content.

Problem

Local commerce users need quick product discovery without losing context around location, catalog, and browsing flow.

Does

Combines product catalogs, Firebase-backed flows, responsive browsing, and local market discovery patterns.

Outcome

Delivered a business-friendly commerce experience for browsing products and location-aware inventory.

Problem

Developers need codebase-aware help, but generic assistants miss project context and produce shallow guidance.

Does

Uses RAG, FastAPI, and LLM workflows to review code, debug issues, generate docs, and answer contextual questions.

Outcome

Improved developer support quality by grounding AI answers in codebase-specific context.

Problem

Manufacturing data can hide failure patterns that are hard to detect manually at scale.

Does

Validates wafer data, clusters patterns, tunes models, and predicts faulty wafers with ensemble ML.

Outcome

Showcased an end-to-end ML workflow for early defect detection and quality-control decision support.

Problem

Material-strength decisions need data-backed estimates before teams commit to costly physical testing cycles.

Does

Analyzes mix ingredients, trains regression models, and predicts concrete strength from material composition.

Outcome

Demonstrated practical predictive analytics for construction-material planning and model evaluation.