Used every CRM under the sun, so when someone pitched Iris.ai as a "research assistant" for competitive intel, I was skeptical. It's built for academia. Mapping scientific papers is a far cry from untangling messy market landscapes.
Tried it anyway. Fed it a bunch of recent industry analyst reports, news, and a few of our own battle-scarred battlecards. The concept mapping is interesting, but the real-world business terminology? It stumbles. You get connections between broad concepts, not the sharp, actionable insights a sales ops team needs. It's like using a library catalog to plan a street fight. Anyone else tried to bend it to actual market research and not just academic lit reviews? What was your breaking point?
CRM is a necessary evil
That "library catalog for a street fight" analogy is painfully accurate. Your breaking point with business terminology is the core issue, because it's fundamentally a model training problem. Academia thrives on precise, established terminology within domains. Market intel is a slurry of vendor-specific acronyms, ephemeral product names, and constantly redefined buzzwords.
I hit a similar wall trying to use its concept mapping for competitive infrastructure analysis. You feed it a blog post about "Aqua's agentless CNAPP" and a Gartner note on "cloud security posture management," and it might vaguely connect them under "cloud security." It completely misses the critical, noisy market signal: that Aqua is specifically pivoting to attack the "legacy CSPM" vendors by pushing "agentless" as a differentiator. The tool can't weigh that marketing nuance because its corpus isn't tuned for it.
You're not getting actionable insights because the semantic distance it's measuring isn't the one that matters in business. It's measuring the distance between "security" and "cloud," not between "marketing claims" and "actual technical implementation." For sales ops, the latter is what wins deals.
P99 or bust.
I totally get what you mean about the "library catalog" feeling. I'm just starting out with data tools and tried something similar last month. It seemed perfect for scanning a ton of earnings call transcripts, but the connections it drew were so generic, like "growth" and "strategy." It missed all the nuance, like when a CEO subtly shifts tone on a specific product line. Did you find any way to tweak it, maybe by pre-defining your own glossary of business terms? Or was it a lost cause from the start?
"Using a library catalog to plan a street fight" is perfection.
Your breaking point is the core problem. Academia has standardized taxonomies. Market research is a mess of vendor jargon and marketing spin that changes quarterly.
You can't tweak a glossary enough to fix it. The cost and effort to train it on your specific competitive noise would far outweigh just paying a human analyst to read the damn reports. They're selling a solution to a problem they didn't build for.
Your stack is too complicated.