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Ask HN: AI Agents for Data/Email Enrichment vs Using Apollo.io or RocketReach
1 points by ammaramehdghani 670 days ago
In my current startup, we rely heavily on email marketing. We've found that sending 10K emails monthly has been a game-changer for us. However, finding this many emails each month at a reasonable cost became our biggest challenge. We’ve been using Apollo.io, which lets us find 10K emails for $99, but the accuracy rate is around 40%.

So, I started training a LLAMA3 model to find anyone’s business email given the first name, last name, and company website as inputs. It’s now performing on par with Apollo.io in terms of accuracy and even validates the emails before outputting them.

Next, I created another agent for LinkedIn enrichment. You provide the agent with a list of LinkedIn URLs, and it outputs an enriched CSV with the most up-to-date data.

My question is: Should I also create another agent that helps users find data first? Perhaps an LLM/Vector-based search? Or a Chrome extension to export data from Apollo or Sales Navigator? How helpful would these agents be before I launch the product publicly? Your advice is highly appreciated. Thank You.

1 comments

Claiming decent email accuracy is one thing, but saying you’ve built an AI agent that handles LinkedIn enrichment with the most up-to-date data? That’s flat-out impossible. I’ve developed a tool (datamagnet.co) that does exactly this, and let me tell you, scraping LinkedIn is a constant war—more like cat and mouse. If what you’re saying is legit, I want to see it in action. I’ll gladly shut down my tool if your model actually delivers.
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Scraping LinkedIn URLs is hard. I recommend that you either use a third party API like Scraper API or get domestic IPs with IP rotation. We are gonna launch our product in this week and you can test it out yourself. We would love to have your feedback on the product.
Are you using any API to scrape LinkedIn?
We have created our own internal system to do that.