[CRM] AI-powered lead scoring with transparent reasoning

I work at a company full of research scientists and AI forecasters. They build tools for AI labs and financial institutions. I kept running into problems in my non-developer day-to-day tasks where I needed exactly the kind of semantic understanding our “deep research” tools provide. But I was trying to solve them with tools built for marketing people: Clay, Apollo, HubSpot, and whatever I could find on Reddit. I finally tried our own tool on what felt like a simple operational task: rank a list of investment firms by how likely they are to pay for research tools. Sharing what worked for me in the hopes it helps someone else dealing with large list management. **My task: I needed to rank investment funds by likelihood to pay for research tools.** This wasn't "company size < 25 = good fit." It required researching each firm, understanding what actually differentiates them beyond the jargon every fund claims, looking for signals of tool usage, figuring out if it's a 1-person shop or a large team. Marketer logic: "if industry = Finance AND employees > 10, add 20 points" Analyst logic: "prioritize firms that value external research tools based on their public communications" Most CRM tools are built for the first one. **Here's an example:** I wanted to prioritize boutique firms where the portfolio manager is also the founder (my thinking was maybe they’d be easier to reach and lead to a simpler sales process; But I also wanted to target larger funds where research analysts have corporate cards and the autonomy to buy research tools without going through layers of approval). **Trying out Clay** In December, I burned 1,912 credits (64% of my monthly budget) on one Clay workbook. At $229/month for 3,000 credits, my enriched table of funds cost \~$57 for 85 firms—before I even got to identifying and enriching contacts. But the larger problem was the iteration cost. As many have called out, Clay has an auto-run setting per column. When it's on, any new row burns credits automatically. When it's off, data goes stale. I'd paste in 50 firms to explore something, and one column with auto-run on would burn 50 credits before I realized it was running. Meanwhile another column with auto-run off was showing stale data I assumed was current. Overall, it was nerve-wracking having to decide how many credits to spend experimenting on different approaches. Do I filter down the list first before enriching it? Often I'd go down one path ("how many job titles does each fund have and do they mention specific paid research tools?") that I ended up abandoning. I mention Clay because unfortunately, I think it’s the closest thing marketers have for these kinds of enrichment tasks, and it’s still expensive and a huge hassle. But enterprise alternatives (from my understanding, I haven’t tried 6sense or others directly) starts around $10K/month and I agree with many of you who described them as black boxes that provide a score but no explanation of WHY an account is prioritized. I have tried manual research with ChatGPT, but at 5 minutes per firm and $50/hour for my time, that's $4.17 per account. For 229 firms: $954 and 19 hours. So obviously not scalable, plus my judgement would differ from the first firm and the last. I’ve also paid for Apollo, Folk, and Hubspot, paying for combinations of these tools with their own credit systems and then still stitching together the workflow (with loads of ChatGPT walk throughs) myself. **What I actually needed was something that resembled an analyst's workflow.** I wanted a tool that could read a firm’s website and understand what they actually do (not just regurgitate jargon), tell me WHY it scored leads a certain way, and not charge me every time I changed my mind. I finally tried the tool my own company builds. The entire workflow cost $28 vs. $145 in Clay (and Clay was just the initial pass (I would have burned more iterating). I'm not going to pitch it here. The point is: if your lead scoring criteria requires judgment, not just filtering by industry and headcount, most CRM tools aren't built for that. They're built for marketers who need to organize high volume lists, not analysts trying to actually understand accounts at scale.