$15K Monthly LLM Spend: AI Gateway Qualification Threshold
We found the qualification threshold. After weeks of dialing CTOs in the AI infrastructure space, the pattern is unmistakable. Spend $15k monthly on LLMs and you'll take our meeting. Spend less than $10k and the answer is always the same: not a priority.
Tarang Vaish at Granica picked up our call last week. He's running multiple large language models in production but no gateway solution yet. Monthly LLM spend sits around $15k. Our rep explained what we do. Tarang didn't say there was an urgent problem. He said yes to a meeting anyway. Wednesday at 2:30 PM PT. Call lasted 634 seconds.
This is the customer profile we're chasing.
Below $10k in monthly spend, the economics don't work. CTOs at that level are still in exploration mode. They're comparing vendors. They're running light workloads maybe two models across one environment. A gateway feels like overhead. Cost savings don't justify adding another tool. Failure risk hasn't materialized because nothing is critical yet. These prospects give us the same answer repeatedly: not a priority right now. We've stopped pushing back. They're right. They're not ready.
Above $15k, everything shifts. You're operating at genuine scale. You're managing four or five models. You're splitting workloads between vendors. You're thinking about cost optimization, vendor lock-in, and redundancy. At this spend level, a gateway becomes infrastructure, not a future nice-to-have. The ROI is visible. The risk of vendor outages is real. The need is legitimate.
Tarang booked the meeting because his company has already decided LLM investment is core to what they build. That decision makes our solution relevant now, even if he's not screaming about today's problems.
We restructured our entire qualification process around this number. Ask about LLM usage and monthly costs early in every call. If the answer is under $10k, wrap it up. Nurture sequence. Don't spend rep energy trying to convince them. If they're at $15k or above, deploy the full playbook. Multiple touches. Technical details. Executive introductions. These are the conversations that close.
This threshold reflects real unit economics. At $15k monthly, LLM costs appear on someone's actual P&L. A 15 percent improvement in spend moves the needle. Better uptime moves the needle. Cost visibility and control move the needle. At $8k or $10k, everything is still noise in a much bigger budget. The financial case to buy doesn't exist yet.
The AI infrastructure market is still forming. Pricing will shift. New vendors will arrive. Spend levels will climb across companies. But right now, in this moment, $15k is the line separating prospects who will seriously engage with our solution from those who won't. It's the line between future customers and companies whose organizations are already committed to the space.
We stopped spending time on sub-$15k prospects. We started focusing on Tarang and customers like him. People whose LLM spending is high enough that managing it properly actually becomes a business problem worth solving.
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