The problem is that Fin prices at $0.99 per outcome. Only for companies with tremendous support volume would it even begin to make sense to build in-house.
There's a wide swath of companies that do < (say) 20,000 cases monthly where the economics will never make sense. And a company finds Fin successful as it grows to 20k/mo, why would it decide to take on the headache as it grows to the 50k/mo? or whatever level where the economics could feasibly make in-house work?
You are right. These outcomes also skew heavily towards the easy stuff for LLMs to get. So tickets that take a human 1 min to respond to now cost you $0.99 ($60+/hour) and you are stuck only doing the hard tickets.
Let's say the small e-commerce business does 500 of these outcomes per month. ~$500 all-in cost at Fin.
I'm curious how you would calculate the other side of the ledger, the in-house approach. Assume the e-commerce business does not employ any AI/ML experts or programmers or anyone whose workday has ever been interrupted by a Github outage (this is the normal case for most businesses, not an artificial handicap). I'm curious how you would structure things to make an in-house more efficient than the $500/mo all-in.
Man you are delusional.
You clearly have never ran a business and don't understand the dynamics of the make vs buy decision.
The dynamics have changed completely in 2026.