PROJECTS / SELECTED ENGINEERING WORK

Real systems. Clear thinking. Measurable results.

Explore Harsh Kumar's full stack development projects: AI-powered SaaS trend analysis, smart calculator platforms, enterprise CRM, real-time systems, and Python automation.

01 / AI-POWERED SAAS

Trend2SaaS

An AI-powered trend analysis platform that converts live market signals into structured SaaS opportunities with problem statements, customer profiles, monetization strategies, and why-now analysis.

The challenge

Process unpredictable trend data asynchronously while delivering clear, useful business ideas and exportable reports without slowing down the product experience.

The solution

Built a Next.js and Python platform with Redis-backed BullMQ workflows, resilient asynchronous processing, structured output generation, and one-click PDF reporting.

The outcome

Achieved 99.9% background job reliability and established a scalable architecture for future AI-assisted workflows and real-time trend processing.

Next.js · Python · Redis · BullMQ · PDF generation · SaaS architecture

02 / PUBLIC PRODUCT EXPERIENCE

Claritools

A practical calculator and guide platform helping users quickly discover useful tools across finance, career, and technology categories.

The challenge

Make a broad library of practical tools discoverable across desktop and mobile without introducing clutter, slow navigation, or confusing information architecture.

The solution

Designed a search-first Next.js experience with keyboard-friendly navigation, responsive layouts, clear content grouping, accessibility, and SEO-conscious page structure.

The outcome

Users can discover relevant tools in fewer than three clicks, supported by a clean and maintainable production frontend.

Next.js · Responsive UI · Search UX · Accessibility · SEO

Additional production outcomes

Enterprise CRM

Reduced sales response time by 40% through real-time lead tracking, notifications, and operational dashboards.

High-performance APIs

Reduced average API response time by 35% by optimizing PostgreSQL queries and Prisma data access.

Automation systems

Automated 90% of manual research tasks through more than fifteen Python-based extraction and workflow tools.

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