# Auditchain Labs Submits Comment to SEC on Regulation Crypto Assets, Calls for Machine-Readable Disclosure and Merkle Root Proof

> Auditchain asks the SEC for machine-readable disclosure in every crypto asset form and a merkle root on a public blockchain for each filing.

- Web page: https://auditchain.com/auditchain-labs-asks-sec-for-machine-readable-disclosure/
- Published: 2026-10-19
- Updated: 2026-10-20
- Author: Auditchain Labs AG
- Publisher: Auditchain Labs AG
- Topics: News, Policy
- Tags: Crypto, Regulation, SEC, submission, Xbrl
- Filing record: [SEC: Comment on Regulation Crypto Assets](https://auditchain.com/about/policy/sec-comment-regulation-crypto-assets.md), filed 2026-10-19

## The 44-page submission asks the SEC to make every disclosure machine-readable and to require each filing to carry a merkle root recorded on a public blockchain.

**WASHINGTON, D.C.**, October 19, 2026 — [Auditchain Labs AG](https://auditchain.com), a provider of global standards based regulatory disclosure automation and validation infrastructure, has filed a comment letter with the U.S. Securities and Exchange Commission (SEC). The letter responds to the SEC’s proposed Regulation Crypto Assets (“Reg CA”). Its main request is machine-readable disclosure: every disclosure should be readable by computers, not just by people.

Auditchain recommends that every form use XBRL, the data format the SEC already uses on EDGAR, its filing system. In addition, each filing should carry a merkle root, a digital fingerprint of its facts, recorded on a public blockchain. As a result, anyone could check that what they read is exactly what the issuer filed.

The SEC’s file number for the proposal is S7-2026-27 (Release Nos. 33-11434 and 34-106150; RIN 3235-AN38). [Read the full submission](https://www.sec.gov/comments/S7-2026-27/s7202627-1098139-3867107.pdf) on the SEC website.

“Disclosure protects investors best when it can be found, compared and checked, and today that increasingly means that software must be able to read it,” said Jason Meyers, Lead Architect of Auditchain Labs AG. “Every Reg CA disclosure should be machine-readable. Each filing should carry a merkle root of its facts, recorded on a public blockchain, so that anyone can confirm that a disclosure is the one filed, complete and unchanged. The disclosures on which investors and the Commission rely should not be the one part of the record that cannot be verified.”

## Why Machine-Readable Disclosure Matters

Under the proposal, only Part I of Form 1-CRYPTO, the notification, would use a structured format. Issuers would file the offering circular, financial statements and exhibits in HTML. The same goes for five other forms in the proposal: Forms NOR, 1-KC, 1-SC, 1-UC and TR. Finally, issuers would post the startup disclosure on a website, in whatever form they choose.

The letter asks for every item of every form to be machine-readable, not only the cover pages. With machine-readable disclosure, the letter says, the SEC would be able to capture every fact in every document, from the first filing to the last. It could also supervise in an automated way. Investors, in turn, could compare offerings and follow what they bought. The letter also notes that investors increasingly read disclosure through software that reads data rather than documents. Examples are brokerage and wallet applications, data services and AI assistants.

## A Merkle Root for Every Filing

Under the letter’s recommendation, the SEC would publish the method for computing each filing’s merkle root. Each root would be recorded on a public blockchain and linked to the root of the issuer’s previous filing. Changing, adding or removing any fact that the root covers changes the root.

Anyone who has the filing can check it without relying on Auditchain or its software. First, they recompute the root from the filing’s facts by the published method. Then they compare it with the root recorded on the blockchain.

## A Working Model of Machine-Readable Disclosure

To show how this works, Auditchain built a draft taxonomy for Reg CA. A taxonomy is the dictionary of a disclosure regime: it defines each fact that filings report. The draft has seven form models, 575 reportable elements and 498 validation rules, and it validates with no errors. However, it is not an official SEC taxonomy, and the SEC has not reviewed or endorsed it.

In addition, Auditchain prepared nine sample filings for one sample issuer, Pacioli Labs, Inc. They show the complete lifecycle, from the first filing (Form NOR) to the last (Form TR), and carry 6,422 facts in all. On October 17, 2026, Auditchain recorded the merkle root of each sample filing on Ethereum. Each sample filing after the first reports the root of the one before. As a result, the nine filings form a chain in which a missing or altered filing can be detected. The sample filings are demonstrations. They are not filings and not offers of securities. Their dates are illustrative, and certain names and facts are placeholders.

### The Nine Sample Filings

| # | Sample filing | Filed | Facts | Merkle root on Ethereum, block and time (UTC) |
| --- | --- | --- | --- | --- |
| 1 | [Form NOR](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c41426e053c/index) | Mar. 1, 2027 | 53 | [Merkle root 1](https://etherscan.io/tx/0x719ae6bcc3b342d2bf1725eba1032f19fed5c624f5c4065dd1ea9c0aa96ef999) Block 26,214,762 at 20:47:47 |
| 2 | [Form 1-SU](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c41d8119445/index) | Mar. 1, 2027 | 893 | [Merkle root 2](https://etherscan.io/tx/0x2c9b1b2429122d3e4c43d85c3b1c6a888962111139f8212fedf3fd335e59b86e) Block 26,214,774 at 20:50:11 |
| 3 | [Form 1-CRYPTO (Tier 2 Node Offering)](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c412d165fe7/index) | Sept. 1, 2027 | 1,169 | [Merkle root 3](https://etherscan.io/tx/0xcd233974a3c8fb6df9032c8655428260a6d6626ef4c0d992c1ebec05b0ea6ff6) Block 26,215,280 at 22:31:47 |
| 4 | [Form 1-SU annual update](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c413af2a864/index) | Jan. 28, 2028 | 1,062 | [Merkle root 4](https://etherscan.io/tx/0xf43687f3a90cbe38a72215944da124b1ad385eacadbb0df18f1fa4d47a9ad856) Block 26,215,287 at 22:33:11 |
| 5 | [Form 1-KC](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c41f3817a4f/index) | Mar. 31, 2028 | 1,095 | [Merkle root 5](https://etherscan.io/tx/0x495425015ebb969618b888226c6adcda1c53e00d6b2f4c653c521f68f861177c) Block 26,215,293 at 22:34:23 |
| 6 | [Form 1-CRYPTO (Tier 2 AUDT Offering)](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c41b2031d6e/index) | Aug. 15, 2028 | 1,253 | [Merkle root 6](https://etherscan.io/tx/0x502ab7404f8a879e2e9b72bd2c7c56c50ae9b3589abb1f7b1a6a58709076bf71) Block 26,215,299 at 22:35:35 |
| 7 | [Form 1-SC](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c41276379c8/index) | Sept. 8, 2028 | 296 | [Merkle root 7](https://etherscan.io/tx/0x08bb7ef879b2b28a345ccfe64d569b71a36a5741047b18b13afdd965da7241e5) Block 26,215,305 at 22:36:47 |
| 8 | [Form 1-UC](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c418dcf2c39/index) | Dec. 22, 2028 | 156 | [Merkle root 8](https://etherscan.io/tx/0x91c01254a7091c0274f8b4a106d0c45a48c11358955eb165f5da4d792daa329a) Block 26,215,311 at 22:37:59 |
| 9 | [Form TR](https://luca.pacioli.ai/luca/view/ac408d76a61c9984077a41efb2ccbe65063aedc070b25b527ec49b787ef00c4126ba86a3/index) | Dec. 29, 2028 | 445 | [Merkle root 9](https://etherscan.io/tx/0x5e85a5755a7acd1c3c09484fd22eef8a501cee8077a8e8c5313c37f800a3707b) Block 26,215,317 at 22:39:11 |
|  | Total |  | 6,422 |  |

*From Exhibit A of the submission. The filing dates are illustrative. Each merkle root link opens the Ethereum mainnet transaction that records the root; block times are in UTC.*

Auditchain prepared these materials with Pacioli.ai, its on-chain platform for preparing and validating structured disclosures.

## Answers to 68 Questions on Disclosure

The SEC’s proposing release asks 154 numbered questions. Sixty-eight of them concern disclosure, and the letter answers each one. Other recommendations include:

- Make the startup disclosure an official form, Form 1-SU, filed with the SEC and posted on the issuer’s website.
- Report every repeating item, such as each risk factor, promise or smart contract, as its own row.
- Let crypto investors reach disclosure in a familiar manner such as the Pacioli Explorer on the condition that they are also filed through EDGAR
- The agency should use the same technical standards as the technology it is supervising and require a chain of merkle proofs across all filings.

Finally, the letter notes that the proposal does not say how markets should trade and hold existing crypto investment contracts. The letter says this leaves disclosure alone to protect investors in those markets.

The letter joins two earlier Auditchain submissions to the SEC, on [Regulation S-K modernization](https://auditchain.com/auditchain-labs-submits-comment-to-sec-on-regulation-s-k-reform-digital-asset-disclosure/) and on covered user interface providers. See the full docket index on the [Auditchain policy page](https://auditchain.com/about/policy/).

## About Auditchain Labs AG

[Auditchain Labs AG](https://auditchain.com) is a provider of global standards based regulatory disclosure automation and validation infrastructure.

[Discord](https://discord.gg/JbpFqKM3EM) | [X](https://twitter.com/auditchain) | [Telegram](https://t.me/Auditchain_Community) | [LinkedIn](https://www.linkedin.com/company/auditchain) | [Facebook](https://www.facebook.com/auditchain/) | [Reddit](https://www.reddit.com/r/Auditchain) | [YouTube](https://www.youtube.com/channel/UC7NlWkYBlsPRZ26e8e2-yKw)

## About Pacioli.ai

[Pacioli.ai](https://pacioli.ai/) is the world’s first web3 and AI enabled regulatory disclosure automation infrastructure for crypto assets. Pacioli.ai enables disclosure infrastructure and disclosure development automation as well as internal and external validation. It enables organizations to prepare financial and non-financial disclosure models and export them in any data format, including XBRL and iXBRL, as required under capital markets legislation.

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