AI generated summary, newsroom reviewed
The 0→1 Doctrine is designed to check an AI action before it runs, so wrong work can be stopped before it costs time, money or data. Band-Based Archive Triage (BBAT) is designed to sort dormant archives, so records with no reason to be kept can be removed and the rest put to approved use. Each works alone or together.
Many AI costs are found late. A wrong action runs, then people spend time finding it, correcting it and explaining it. Stored data works the same way. Records that nobody uses still cost money to hold, and they can be exposed, caught in a legal dispute or simply forgotten. The two inventions work at different points: one before an action, the other on data already stored.
The 0→1 Doctrine is designed to place each measurable value on a scale from 0 to 1 and compare what is needed with what is allowed before an action runs. If the ranges do not match, the action can be changed, rerouted, held or halted. A check at this point can reduce time spent on work that would later fail, rework after the fact, and errors from mismatched units or rules.
Each governed action ends in a sealed receipt, so evidence for an audit or a dispute is produced as the work happens, not rebuilt afterwards. That can reduce audit effort and narrow a dispute to what the receipt shows.
Example, illustrative only: a supplier’s part falls outside the buyer’s stated limit. The check holds the order before dispatch, so transport, handling and return costs may never arise. A process that uses energy or material can likewise be set to start only after approval.
Each check is designed to use bounded computing, and checks can be shared across systems as decisions grow in number. The same check can run on classical computers, AI accelerators, offline devices or paper tokens where connection is limited.
A dose, a delivery time and a file’s age in storage use different units. Each becomes a value from 0 to 1, so AI can read them all the same way. A fit score on the same scale can decide the action.
The Doctrine is designed to turn raw values into bands near where they are produced. Where configured, only the band travels, not the raw record. That can reduce the data sent over networks and the identity-linked data copied, and it can lessen the need for one large central store where device-level storage is enough. Each receipt is a compact digest, not a copy of the data.
Dormant archives cost money while they sit unused. BBAT is designed to read only metadata, the labels on a record, and route the record to keep, delete or use. Records that are redundant, obsolete or trivial can be found this way without opening their content.
Where deletion is carried out under the configured rules, storage cost can fall, and so can the energy used to hold the data. Fewer stale records can also mean less exposed in a breach and less to review in a legal matter. BBAT is designed to connect through metadata interfaces, so a full migration of storage may not be needed.
BBAT is designed to compare resource use before and after deletion and to record that estimate with the sealed receipt. A reduction then becomes something a team can check, not something it assumes.
A record under legal hold goes to an authorised reviewer, not to deletion or release. The reviewer decides without seeing the content. Each deletion, release and batch leaves a sealed receipt that holds no record content, and an authorised auditor can check a receipt without access to the archive.
Proof of deletion can match the risk: a logged procedure, a cryptographic comparison of the state before and after, or a certificate from the secure environment. A correction gets a new receipt linked to the old one, and the old one stays.
Rules differ between countries. BBAT is designed to apply a configured jurisdiction order, using the most protective standard, and to seal the result. Conflicts of law still go to an authorised reviewer.
Some records are worth using. BBAT is designed to reduce a group of records to one bounded band inside the secure boundary and release only that band, with a receipt. The records stay with their holder. Release is designed to be suppressed when the group is too small or when the band could be linked to outside data. These bands can also become AI training signals.
In the Doctrine, a value that cannot be computed halts the chain until a named person resolves it. In BBAT, low-confidence, legal-hold and protected-category records go to a reviewer. Routine cases can be handled by the checks, so expert time goes to the cases that need it. Humans set the ranges and decide exceptions.
AI agents can act in groups. The Doctrine is designed to check each agent’s action before it runs. The BBAT filing describes supervising agents from sealed receipts alone, to flag harm that appears only when several agents act together. Where agents can spend money, a check first can reduce exposure to unauthorised cost.
Whatever intelligence comes next, the best moment to govern it is before it acts. Cost met early, value drawn from dormant data, capital checked before it moves.
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This can be tested, live, via API, governed against ungoverned, side by side.
Systems theorist, inventor, and serial entrepreneur Vatsal Soin holds grants in the US, Japan, India and more; filings span six continents; latest grant, AI footwear, August 2026. Inventions: footwear, apparel fit, Sharable Size Cards, digital twins, robotics, global governed data, archive triage, quantum-resilient cryptography, AI governance. SIM–RMIT and NTU alumnus. Every prior invention was a step; 0→1 is the destination.
Granted: US Patent 12,446,652 B2 · Japan Patent 7560909 · India Patents 454081 and 599317. Filed: PCT/IN2025/051943 · US 19/489,595 · India 202511115781 · Australia AU2022450649 · India 202611113867 (23 September 2026) · PCT/IN2026/052042 (1 October 2026).
Informational only. Not certified. No endorsement implied. Not investment advice. Examples are illustrative, not field results. Vatsal Soin · © 2026 All Rights Reserved.
