Editor’s Note: This blog captures the AI Am Legends hackathon showcase at the Geekathon, featuring their project, Lead Magnetify, an AI-powered B2B lead generation tool. Led by Shrutika Swaraj and developed by a team of five, this innovative solution simplifies business matchmaking by automating lead identification and engagement. The following sections reflect the team’s insights into their development journey and key technological implementations.
Team composition: List of team members Shrutika Swaraj, Monisankar Nath, Logeshwaran, Khushi verma, Nishant P
The problem we tackled in this hackathon was generating B2B leads efficiently—a challenge many businesses face when searching for potential clients. Identifying the right leads is time-consuming, so we built an AI-powered tool to streamline this process. The name of our product is Lead Magnetify.
Our solution filters potential leads based on key parameters such as industry, funding, and company size using data from Crunchbase. We ensured compliance by following ethical data scraping practices and limited access regulations.
How It Works
We collect company details from Crunchbase, perform import-export operations, and apply filtering mechanisms to sort companies by industry and funding. This gives us the most relevant potential leads.
A business user no longer needs to spend hours manually searching for clients. Our platform automates this process, matching businesses with the right connections effortlessly. Once potential leads are identified, users can engage them by sending personalized emails generated using AI. We even provide a reminder system to schedule follow-ups, ensuring timely communication.
This is like business matchmaking powered by AI, helping businesses build strong B2B relationships while boosting lead quality and conversion rates.
Tech Stack
To bring Lead Magnetify to life, we used:
- Next.js – For a super-fast and scalable frontend.
- ChatGPT API – To generate tailored email content based on LinkedIn posts.
- Shadcn UI Components – For a clean, reusable, and interactive UI.
- Vercel – For seamless deployment and hosting.
- Puppeteer – To fetch LinkedIn comments for AI analysis.
- OpenAI API – To analyze collected data and generate potential leads.
Project Flow
- Data Collection – We extract company details from Crunchbase.
- Filtering & Sorting – Leads are sorted based on industry, funding, and company size.
- AI-Powered Engagement – The tool fetches LinkedIn posts and analyzes comments using OpenAI.
- Personalized Email Generation – AI drafts customized emails based on a company’s latest activity.
- Lead Profiles & Engagement Tools – Users can view potential leads, their contact details, and initiate outreach.
- Future Scope – We plan to integrate LinkedIn Lead API and expand to more data sources for a richer lead pool.
Showcasing Lead Magnetify
With this tool, users can search for companies based on three key parameters: industry, company size, and region.
Upon hitting ‘Search,’ a list of companies matching the criteria appears, displaying essential details like total funding, last funding date, a brief description, and a link to their official website.
For engagement, we provide an option to generate AI-powered personalized emails. By analyzing LinkedIn posts and comments, the AI crafts customized outreach messages. In the future, we aim to integrate direct email-sending capabilities and fetch data from additional platforms.
Our tool also includes lead profiles, where users can access details of key contacts, including their roles and services they’re interested in. Clicking ‘View Details’ reveals more insights, making it easy to initiate meaningful B2B connections.
Final Thoughts
Lead Magnetify is an end-to-end AI-powered solution that enhances lead quality, boosts conversion rates, and simplifies business networking. With our efficient, AI-driven, and user-friendly approach, businesses can focus on what truly matters—growing their network and driving success.
GitHub link for the project: https://git.geekyants.com/ai-am-legends/ai-am-legends-frontend
