Qlucent.ai

Inspiration

Navigating the landscape of Enterprise, SaaS and open-source tools is overwhelming. We wanted to create an intelligent, unified platform that makes tool discovery, comparison, and implementation seamless — especially for teams that need reliable, fast recommendations without spending hours researching.

What it does

Qlucent.ai is an AI-powered platform that empowers users and businesses to discover, compare, and deploy the best open-source and enterprise tools—faster and smarter. It provides:

• Personalized recommendations using AI-based semantic search and tagging
• Use-case-based tool bundling for quicker decision-making
• Ready-to-deploy environments via Qlucent-managed infra or Bring Your Own Cloud
• Verified vendor listings for enterprise-grade support
• GitHub-based tool discovery, allowing users to explore and deploy from public and private repositories

Whether you're a developer, decision-maker, or a startup founder, Qlucent streamlines your tool evaluation and deployment journey—from days to minutes.

How we built it

• Frontend: Built using Bolt.new, styled with Tailwind, hosted on Netlify
  
• Backend: FastAPI deployed via GCP Cloud Run, integrated with Qdrant for vector search, and Supabase for authentication.
  
• AI Models: SetFit for auto-tagging, sentence-transformers for embeddings, with scraper pipelines for G2, GitHub, and Product Hunt.

Challenges we ran into

• Building a clean embedding + recommendation pipeline with live data
  
• Memory constraints on Cloud Run with large model inference
  
• Managing fine-tuning, deduplication, and search relevance across multiple sources

Accomplishments that we're proud of

• Successfully launched live backend and frontend in just a few days
• Built a real-time scraping and enrichment pipeline for continuous tool discovery
• Seamlessly integrated AI-powered tagging, semantic search, and recommendations into a no-code frontend (Bolt.new)
• Enabled GitHub-based tool discovery with support for both public and private repositories for one-click deployments
• Added support for Qlucent-managed deployments as well as BYOC (Bring Your Own Cloud) via user-provided cloud credentials

What we learned

• Bolt.new makes rapid frontend development very intuitive
  
• Vector-based search with semantic tagging drastically improves tool discovery
  
• Cloud-native architecture using GCP + Supabase scales well even during rapid development

What's next for Qlucent.ai

• Build community-curated bundles
  
• Launch a marketplace for verified tool vendors
  
• Add pricing intelligence and stack ROI insights
  
• Let users deploy full stacks with 1 click
• Train and fine-tune LLMs on curated tool datasets for smart querying and tagging
  
• Auto-generate personalized tool stacks based on industry, team size, and budget
  
• Launch an AI copilot to assist with tool selection, integration, and setup

Built With

• claude
• cloudrun
• cursor
• gcp
• github
• openai
• qdrant
• supabase