The problem :

Pre-call research takes time most sales reps don't have. Before a discovery call, a good rep needs to know the company, the prospect, the tech stack, the competitive landscape, and the likely objections. In practice, that means 30 to 60 minutes of browser tabs, LinkedIn scrolling, and manual note-taking before every single call. The reps who skip it walk in underprepared. The reps who do it properly are spending hours a week on work that has nothing to do with actually selling. Either way, the business loses.

Approach :

I built a sales research copilot in Relevance AI with three connected tools working in sequence. The first scrapes the company website and returns a structured summary of what the business does, how it positions itself, and what technology it appears to be running. The second takes a LinkedIn URL and builds a prospect profile covering role, background, and likely priorities. The third synthesises both into a structured pre-call report: talking points, relevant context, and suggested angles for the conversation, generated and ready before the rep picks up the phone.

The whole process runs in minutes, not hours. Reps input a company URL and a LinkedIn profile. The agent handles the rest.

The result:

Research time dropped significantly. Reps walked into calls with accurate insight into the tech their prospects were already using, which changed how they structured conversations from the first minute. The work that used to sit between booking a call and having one, the part nobody was ever allocated time for, now happens automatically.

"Saved me hours pulling data together and gave me a clear picture of the tech already in play. I knew exactly how to structure my calls going in."