#opg $OPG
Your AI vendor just gave you garbage output. What are you going to do about it?
File a support ticket.
Wait 3 business days.

Get a copy paste apology and maybe a credit refund if you're lucky.That's the current state of AI service agreements. Billion-dollar APIs operating on the honor system.
Think about what an SLA actually means in traditional software.@OpenGradient

If AWS goes down for 4 hours past their uptime guarantee, you can prove it happened. There are logs, timestamps, independent monitors. The violation is real and documented.Now try proving an LLM gave you the wrong output at 2:14am on a Tuesday.

You can't. The inference happened in a black box. No receipt. No witness. No record.
This is the problem OPG is quietly solving.

On-chain proof of inference creates a cryptographic record of exactly what input went in, what model processed it, and what output came out.

It's not a log file some company controls. It's math. Publicly verifiable math.
Here's where it gets genuinely interesting.When inference is recorded on-chain, SLA violations stop being a "he said, she said" conversation between you and a vendor support team.
They become mathematically provable events.

Which means they can be written into smart contracts. Which means enforcement becomes automatic. Which means the power dynamic between AI vendors and their customers shifts for the first time ever.
We're not talking about a feature update.
We're talking about accountability infrastructure.

The kind of thing that has to exist before enterprises will ever trust AI with mission critical decisions at scale.
Right now, every company using AI APIs is flying blind on quality guarantees. OPG is building the instrument panel.

What would you pay for a guarantee that an AI API actually delivered what it promised with automatic compensation if it didn't?
That question is about to have a real answer.
#opg #OpenGradient #square $VELVET $TERMINUS