A model that sets a limit, a rate, or an eligibility call directly in the user flow
What you can’t sign off
The AI you ship faster than you can stand behind it.
When the AI is the product, its failures aren’t internal incidents — they’re customer-facing, public, and fast. These are the calls that go out before anyone can prove they’re controlled.
The regulatory picture
A bank’s obligations, at a startup’s velocity.
You carry the same obligations as a bank — RBI, the EU AI Act for high-risk decisioning, DPDP/data rules on the customer data your models run on — but at startup velocity, often without a model-risk function.
The exposure isn’t that you lack a policy. It’s that your product ships AI decisions faster than anyone can prove they’re controlled.
When the AI is the product
Its failures aren’t internal incidents. They’re customer-facing, public, and fast.
What Qapitol assures
Assurance as part of your build, not a gate bolted on after.
Evaluate the models in the product, control the workflows that act, and produce the evidence that lets you scale the product without scaling unproven risk.
Evaluate the models in the product
The lending decision, the assistant, the risk engine — assessed where they actually act, in the user flow.
Control the workflows that act
The agents and decisioning that ship faster than review get the guardrails, overrides and checks that make them safe to run.
Produce the evidence to scale
The proof that lets you grow the product without scaling unproven risk — assurance as part of the build, not a gate bolted on after.
Proof