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Use cases

The AI you can't see is the AI you can't defend.

Most AI risk today is invisible, running outside your controls, inside your vendors, or acting on its own. These are the risks every organisation shares. The same signed receipt that verifies your AI savings turns each one from a blind spot into something you can prove.

Shadow AI

The tools you never approved.

Staff paste customer data, code, and financials into consumer AI with no oversight. One in five organisations has already been breached through shadow AI, at a cost of roughly $670K more per incident (IBM, 2025). You can't govern what you can't see.

AskLedger surfaces and records every AI call, including the ones bypassing your gateway, so you can detect leaks and prove control.
Third-party / Vendor AI

Your vendor's model, your liability.

A supplier quietly adds an AI sub-processor in a routine update, and it now touches your customer data. You stay accountable, but you cannot see what their model actually did, or enforce your data-processing agreement with anything but trust.

Verify exactly what a third-party AI did with your data. Prove it touched only permitted fields, enforced with math instead of a promise.
Agentic AI

Agents that act on their own.

Autonomous agents move money, change records, and call tools. When every individual action looks legitimate, misuse and drift stay invisible until after the damage is done, and ordinary logs can be altered by whoever gained access.

A tamper-evident record of every agent action, for detection, forensics, and control, checkable long after the fact.
Unverifiable output

Confident, and sometimes wrong.

Hallucinations slip into real decisions, and ordinary logs can be edited after the fact, so they don't survive an audit, a regulator, or a court. A confident number and a defensible number are not the same thing.

Signed evidence of exactly what the model produced, provable months or years later, with only a public key.
Data protection

Prove your data stayed yours.

Everyone sells "block the leak." No one can prove it never happened. AskLedger gives you a tamper-evident record of exactly what data each AI touched, so you can prove it was never sent, retained, or trained where it shouldn't be.

"Is our data training someone's model?"

A signed receipt of every AI-data interaction shows exactly what was accessed, and proves it wasn't retained or used to train.

"What is our vendor's AI doing with our data?"

Verifiable proof a third-party AI touched only permitted fields, so you enforce your DPA with evidence, not trust.

"Staff are pasting secrets into public AI."

A record of the data-to-AI boundary, so you can detect leaks, prove control, and show regulators you have it.

"Prove nothing was kept or left the region."

Tamper-evident evidence of what happened at each step, provable later, with only a public key.

Turn every AI blind spot into evidence.

See how receipts work, or talk to us about the risks specific to your stack.