Full-Stack developer / AI Engineer
A large-scale AI discovery and career intelligence platform that aggregates AI tools from across the web, enriches them with AI-generated metadata, and maps them to careers, tasks, and automation potential—helping professionals understand how AI can automate their daily work.
"AI discovery becomes significantly more valuable when paired with structured ingestion pipelines, intelligent categorization, and measurable automation impact."
AI tools are fragmented across the internet with inconsistent descriptions, unclear use cases, and no practical mapping to real-world careers or tasks. Professionals and teams struggle to identify which tools matter to them and how much of their work can realistically be automated.
Built an AI-powered platform that continuously ingests AI tools via web scraping and spreadsheet-driven workflows, generates and normalizes metadata, categorizes tools by career and task, and computes automation scores that quantify automation potential at both role and task levels.
The backend is built with FastAPI and orchestrates ingestion, enrichment, and discovery workflows. AI tools are ingested via Firecrawl-based scraping pipelines and Google Sheets integrations for low-friction submissions. Structured data is stored and managed using MongoDB and Airtable. Algolia powers fast, relevance-tuned search across tools, careers, and categories. The frontend consumes a unified API optimized for SEO, discoverability, and content indexing.
TAAFT is an AI tools discovery and career automation intelligence platform.
The system aggregates AI tools from across the web using automated scraping pipelines and spreadsheet-driven ingestion workflows. Admins and contributors can submit tool URLs directly via Google Sheets, which are automatically picked up, scraped, enriched, and added to the platform.
Each tool is processed using AI models to generate structured metadata, normalize descriptions, and assign categories, tags, and use cases.
From the user perspective, the platform supports multiple discovery paths:
• Browse AI tools by category or use case (e.g. content creation, automation, image editing). • Search by profession (e.g. tester, marketer, designer) to view relevant careers and top AI picks. • Explore career detail pages that display an overall automation score, a breakdown of job categories and tasks, and task-level automation scores derived from available tools. • Expand individual tasks to view the specific AI tools contributing to automation.
The platform also includes an AI & machine learning glossary with tag-based learning paths, an SEO-optimized blog system (AI-generated, scraped, and human-written), and advanced category browsing with filtering and full-text search.
Each tool detail page includes enriched descriptions, scraped media, user ratings, and outbound referral links used for monetization.
Duration
4 Months
Team Size
2 people
Impact
Built a scalable ingestion and discovery system aggregating thousands of AI tools, enabling career-level automation scoring, and supporting referral-based monetization through AI-driven search and categorization.
Case studies in similar engineering domains.
Engineered a modular, production-grade backend framework designed specifically to power AI workspaces. Implements robust token caching, graceful rate-limit handling, circuit breakers, and WebSockets for real-time state streaming.
A full-stack performance management platform that enables clear goal setting, evidence-based execution tracking, fair evaluations, and transparent performance-linked payouts—built entirely on Next.js with a strong audit and access-control foundation.
Async multi-provider AI content generation framework for music, video, and images with plugin providers, style presets, CLI workflows, job tracking, duplicate detection, and cost controls.