AskLedger turns every AI decision into a signed receipt, so when a regulator, auditor, or court asks what your AI did, you can prove it independently, without asking anyone to trust you.
Built for banking, insurance, and healthcare, and for the agentic AI now acting on its own.
$ npx @askledger/receipts-sdk verify receipt.jsonAI is now in nearly every business function, incidents are climbing, and transparency is falling, exactly as regulators begin to demand evidence of what each system decided and why. The obstacle is rarely the model. It is that organizations have no reliable, independent way to prove what their AI actually did when an auditor, regulator, or court asks.
| Figure | What it means | Source |
|---|---|---|
| 88% | of organizations now use AI in at least one business function | Stanford HAI, 2026 |
| $581.7B | in global corporate AI investment in 2025, more than double the year before | Stanford HAI, 2026 |
| 362 | AI-related incidents logged in 2025, up 55% year over year | Stanford HAI, 2026 |
| 40 | Foundation Model Transparency Index score out of 100, down from 58 the year before | Stanford HAI, 2026 |
AskLedger closes that gap. It turns each AI decision into a signed, tamper-evident receipt, so you can prove what your AI did in evidence anyone can check, without asking them to trust you. See how → And what it does not prove →
From a solo builder to a global enterprise, AI is now everywhere in the work, and almost no one can say what it's actually doing. Ask yourself:
Your people, your apps, service accounts, and agents acting on their own.
Every model, data source, and permission actually in play.
The true bill: subscriptions, usage, retries, review and rework.
The business outcome, or the exposure, behind each AI action.
When an auditor, regulator or customer asks, you need proof, not a claim.
AskLedger answers the one question that makes the other four matter: can you prove it? Without cryptographic proof, the other four are just claims. With it, they are evidence anyone can check.
A signed receipt for every AI decision, across five language SDKs, hash-chained and independently verifiable. Not a log you keep and could edit, but portable evidence an outsider can check without trusting you.
Verifiable by anyone with a public key. No account, no trust in us, no trust in the vendor. Change one character and verification fails.
Open source, Apache-2.0, built on published RFCs. A trust layer you have to take on faith is not a trust layer, so ours is inspectable, end to end.
Any model, any provider, any gateway, any region. It sits above what you already run instead of replacing it.
Receipts record a hash of the input and output, not the raw content. The private signing key stays inside your own HSM.
Proof is the core. Around it sits a five-layer accountability model, from preventing the wrong action to enabling the program that governs it. See the five layers →
AskLedger sits above the tools you already run, importing their traces, costs and signals, then adding identity, policy, outcomes and independent proof. We connect your stack; we don't ask you to rip it out.
Like declining your loan or flagging a payment. It happens in a split second.
It records exactly what the AI did, and when. Just like the receipt you get at a shop.
A regulator, your bank, or you. Change even one word and it stops verifying.
That's AskLedger: a receipt for what AI does.
Pick an example, watch AskLedger lock it, then try to change it and see what happens. Real cryptography, running right on your device.
A computer checks these automatically. The moment the two fingerprints stop matching, the signature fails. That's how tampering is caught, without trusting anyone.
The SDK, the CLI and the verifier are open source under Apache-2.0. Three ways to try them right now:
Sign a receipt, tamper with it, and watch verification fail, live in your browser. Nothing to install.
Open the playground →Verify any receipt from the command line, no install needed.
One import, five languages, an independent verifier in every SDK.
India's RBI has closed consultation on its Model Risk Management guidance, the UAE CBUAE deadline follows within weeks, and the EU AI Act's high-risk logging duty lands in December 2027. Each one asks for evidence of what an AI system did. It's the record most institutions can't yet produce.
It isn't only regulated industries. Any team putting AI into real decisions gets the same advantages, starting on day one.
Pass security reviews and RFPs with cryptographic proof a buyer's own team can check, instead of a claim they have to take on faith.
Accountability becomes one line of code, not a six-month compliance project. Stop stalling in pilots.
Verifiable evidence lets you file a claim, price a policy, or hold a vendor liable when AI gets it wrong.
When a vendor's model touches your data, prove exactly what it did, and keep accountability where it belongs.
As agents act on their own, get a tamper-evident record of every action for forensics, drift, and control.
One evidence layer supports the record-keeping obligations across the frameworks coming: EU AI Act, RBI, NIST AI RMF, ISO 42001. Evidence, not a compliance guarantee.
Real scenarios, end to end, the decision, the moment it's challenged, and the evidence a receipt gives you.
Prove why a model declined a loan or blocked a payment, to a regulator or a court.
Explore → InsuranceDefend AI pricing and claims decisions with signed, verifiable evidence.
Explore → HealthcareShow what AI recommended, when, and on what data, without copying PHI.
Explore → GovernmentAutomated decisions that are auditable and appealable by design.
Explore → LegalA defensible, reproducible record of what legal AI produced.
Explore → All sectorsSee how receipts translate across every regulated sector.
Industries →EU AI Act, India's RBI, UAE CBUAE, US NIST, UK, APAC, ISO 42001. AskLedger produces the portable, signed evidence these frameworks ask for, built on published RFCs so a receipt holds up across jurisdictions. The mappings are ours, written from each regulator's published text and not reviewed by any regulator. It supports compliance; it does not replace it, and legal sufficiency always depends on your use case and your counsel.
"The next five years of AI are not about better models. They are about the infrastructure that makes them defensible."
Built in the open, because trust infrastructure should be inspectable. Open-source core under Apache-2.0; a commercial layer (hosted verification, a regulator portal, and evidence packs) is in design-partner preview.
No. Receipts record a hash of the input and output, not the raw content. The private signing key stays inside your HSM, and verification needs only the public key. Nothing confidential is exposed to produce or verify a receipt.
The cryptographic cost of a receipt is under a millisecond: canonicalize, hash and Ed25519 sign total about 0.4 ms. Receipts are emitted off the request path, so that cost never blocks the AI response, and it is noise against a model call that takes hundreds of milliseconds. Durable persistence is separate: the file-backed reference SDK fsyncs each write for crash safety, which is hardware-dependent and around 10 ms on a laptop SSD, while production uses Postgres where it is a batched commit. Verifying takes about 1.8 ms and normally happens later and offline, when someone audits the record. Reproduce the crypto numbers with npm run bench. Receipt generation never blocks or breaks the AI call it instruments.
No. AskLedger is open source under Apache-2.0, the wire format is an open specification, and any third party can verify a receipt with published RFCs and a public key. The protocol is a public good; adoption is the moat, not lock-in.
OpenAI, Anthropic, Gemini, Bedrock, Cohere, Mistral and more via drop-in adapters, plus LangChain, Cursor, and gateway integrations, across five language SDKs. A generic adapter covers any HTTP-based provider.
As a library inside your own environment, no data routed to a third party. Signing uses your existing AWS KMS, Azure Key Vault, GCP KMS, or PKCS#11 HSM. Chain state runs on your Postgres for multi-tenant scale.
You can build a log. But a record you generate yourself, you can also edit, delete, or backdate, so it won't hold up when someone disputes it. AskLedger produces a signed record that cannot be altered without the change being detectable, and that an outsider can verify without trusting you. Capturing what happened is the easy part; proving it is what we solve.
Ordinary logs are editable and only mean anything inside your own systems. A receipt is tamper-evident (change one character and verification fails) and independently checkable by anyone with a public key. A log is a claim; a receipt is evidence.
Our own format, and we would rather say so plainly. It is an open specification, published and Apache-2.0 licensed, written as a candidate for standardisation. No standards body has adopted it. What is standardised is everything underneath it: RFC 8785 for canonical JSON, Ed25519 for signatures, RFC 3161 for timestamps. So you are not trusting an AskLedger invention to verify a receipt, you are trusting published cryptography plus a spec you can read. We also publish mappings to ISO/IEC 42001, the EU AI Act, India's RBI guidance and NIST AI RMF, which we wrote ourselves from the regulators' published texts; no regulator has reviewed or endorsed them.
Where AI accountability meets the real world, the decisions, risks, and regulations shaping how enterprises prove what their AI does.
KPMG, Deloitte and EY all pulled or refunded reports after their AI fabricated citations. The missing layer was provable provenance.
Read →Why cryptographic receipts are becoming the record AI credit decisions need as model-governance expectations tighten.
Read →As SOCs hand more decisions to AI, tamper-evident records become the only trustworthy account of what an autonomous agent actually did.
Read →Every AI-accountability deadline that matters, EU AI Act, India RBI, UAE CBUAE, NIST AI RMF, ISO 42001, in one place, with the evidence each one demands. Know what's coming before your auditors ask.
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