Building Querative - Simplifying Complex Searches

Recently, I launched Querative, a SaaS product designed to simplify complex online searches using natural language queries. Here's a look into how it came to be.

The idea for Querative stemmed from my own frustrations with advanced search techniques. I often found myself spending too much time crafting complex search parameters, especially when looking for business contacts and emails. I thought, "What if there was a tool that could do this automatically?"

Querative transforms natural language queries like "managers in New York with email on LinkedIn" into optimized search parameters. It then opens the refined search results directly in a new tab, saving users time and effort. Importantly, Querative doesn't scrape data, keeping it compliant with platform rules.

Building Querative was a journey of learning and problem-solving. I chose a modern tech stack to bring my vision to life:

  • Frontend: ReactJs, NextJs, Tailwind CSS, and DaisyUI for a responsive and sleek user interface.
  • Backend: Next.js Serverless functions to handle query processing.
  • Database: MongoDB (Atlas) with Mongoose as the ORM for flexible data storage.
  • Authentication: Authjs to ensure secure user access.
  • Payments: Lemon Squeezy for hassle-free transaction handling.
  • Hosting: Vercel for seamless deployment and scaling.
  • Analytics: Plausible for privacy-friendly user insights.

Each technology choice was deliberate, aimed at creating a robust, scalable, and user-friendly product.

The development process wasn't without its challenges. Optimizing the query transformation algorithm and ensuring accurate results across various platforms required several iterations. However, each obstacle overcame led to a more refined product.

Looking ahead, I'm excited about Querative's potential. I plan to expand its capabilities to cover more platforms and introduce advanced features based on user feedback.

Building Querative has been a rewarding experience, reinforcing the importance of solving real problems and continually iterating based on user needs. It's a reminder that sometimes, the best products come from our own pain points.