Human mediation
The founder mediates the act and preserves the scope, record, and human coordination of the debate.
Promoting the Global Debate
The American Cross-Examination Institute, Applied to AI Model Training and Self-Regulation.
Cross-Examination — the adversarial discipline born in American courts — is now applied to AI governance in Brazil. Where regulation has not yet arrived, self-regulation must fill the gap. This platform brings sensitive topics to the public arena, invites developers and users to debate, and creates a structured process where AI claims face the same rigor as courtroom testimony. The goal: unite the ecosystem to resolve conflicts transparently and build accountability where the regulatory vacuum exists.
Decision first
The public record starts with the issued operational decision.
Delta Cross-Examination enters the site as a concrete public vehicle: a place for dialectic review, developer debate, firmed theses, and audit memory. The decision is placed first so every later argument, session, and publication artifact is read against the same boundary.
Star Compliance Shield
Public result for the May 16, 2026 session.
The mediation was conducted in Portuguese under mandatory human record. The goal of this Session 001 was to solidify our operational compliance regulation (Norms 1, 2 and 3), establishing the pillars of source protection, human gate, and certified cryptographic linkage.
No provider endorsement
AI models from different providers contribute auditable technical opinions, not institutional approval.
Dialogue and free enterprise
The session promotes public debate, free initiative, and responsible contradiction around AI self-regulation systems.
Developer listening
Invited developer views are treated as qualified inputs for thesis formation, critique, and method improvement.
Auditable record
Relevant outputs should be preserved with logs, hashes, dates, scope, and chain-of-custody notes before publication.
Institutional respect
The debate does not replace counsel, regulators, public authorities, or official institutions; it organizes prior technical reflection.
Transparency rule
No “AI endorsement” claim without a verifiable record.
Any reference to a model must be published as an auxiliary technical opinion, with human mediation, date, scope, limitations, and artifact hash.
- Session language
- Portuguese
- Format
- Public pilot session
- Human decision
- Required
- Publication
- After review
The proposition
A self-regulation system for AI accountability, collegial decisions, and developer debate.
Delta Cross-Examination is not a website about RAG DATA. It is a self-regulation platform coordinated from that foundation to foster public dialogue, free enterprise, and serious listening to developer perspectives. AI claims can be opened as review records, tested through adversarial review, and converted into firmed theses when the record supports them.
The RAG DATA seven-step discipline supplies the integrity layer. Delta Cross-Examination supplies the institutional layer: debate, procedure, developer participation, and public-facing collegial decisions.
Technical model record
AI-assisted contribution registered for the public session.
This site was conceived, coordinated, and mediated by the human founder. Enterprise AI models assisted with technical review, visual structure, copywriting, trilingual localization, record organization, and the integrity packaging.
The record does not state provider endorsement, does not replace human professional review, and does not disclose the internal working environment. For enterprise compliance, every relevant public change should create a new hash batch, review record, and human validation.
Miriam Mesquita Reis conducts the thesis, mediation, scope, and publication decision.
Enterprise AI models assisted with design, content, localization, static architecture, manifests, logs, and batch signing.
Future versions should preserve chain of custody, human review, and batch signature before publication.
Startup proposal
A practical AI self-regulation system for enterprises, developers, and public-interest review.
The proposal documented in the project package frames Delta Cross-Examination as an operational system, not only a concept: open a review record, test it under contradiction, and publish a firmed thesis with documented conditions, dissent, and revision pathways.
Intake, evidence anchoring, thesis, cross-exam, consensus, firming, and publication.
Versioned thesis journal with validity scope, overruling criteria, and decision records.
Debate tracks, audit templates, model-role experiments, and controlled challenge rounds.
Operational regulation
Enterprise-ready AI compliance regulation in clear operational language.
Regulation v1 defines how the system runs in production: source protection, human-gated AI audit, certificate-bound cryptographic linkage, and versioned collegial decisions with documented dissent.
References are hash-based and controlled. No public source mirror and no sensitive metadata indexing.
AI-to-AI review is valid only with a named human coordinator and custody-ready event logging.
SHA-256 batch manifests and model linkage are valid only after official certificate verification.
Developer access
Developer dashboard.
A concrete operating surface for sessions, challenge rounds, and firmed theses under institutional respect, including governance language aligned with the Brazilian Bar Association.
2
Structured review sessions with traceable evidence intake and cross-exam checkpoints.
4
Versioned outcomes with scope limits, dissent entries, and revision triggers.
Green
Human gate, certificate linkage, and chain-of-custody controls currently enforced.
Brazilian Bar Association
Public statements are governance records and do not replace counsel, public authorities, or official institutions.
Public debate vehicle
A tangible forum for dialectic, decision records, and audit memory.
This area turns the method into an operating vehicle: each claim can be challenged, answered, synthesized, and tied to a public memory log without turning the site into a model-training record.
Thesis, antithesis, synthesis
Structured debate sessions keep disagreement visible until the record supports a responsible synthesis.
DCE-2026-05-16-001
The working record approves this site as a public self-regulation vehicle for debate and audit memory.
Append-only chain
Normative basis, dashboard creation, signature controls, and deploy readiness are hash-linked.
GDPR Certified
The founder holds a GDPR (General Data Protection Regulation) certification, ensuring data protection compliance across all governance activities.
Operational decision record
Decision issued for the public vehicle.
The record states that Delta Cross-Examination is a public-facing self-regulation vehicle for AI accountability debate. It preserves institutional respect, human coordination, and cryptographic auditability.
- Status
- Issued
- Scope
- Site vehicle
- Human gate
- Required
- Training claim
- Not applicable
A claim is opened with source, scope, risk, and proposed interpretation.
Developers, auditors, or invited reviewers challenge assumptions and missing evidence.
The record separates consensus, dissent, validity limits, and revision triggers.
Only bounded outputs with audit links and human coordination become public records.
Debate promotion
Open structured debate sessions for invited developers and guests.
Debate is promoted through clear intake, scoped challenge prompts, and publication criteria that separate experimentation from institutional claims.
Model Accountability in Finance
Challenge assumptions, test evidence sufficiency, and map residual risk for high-stakes outputs.
Temperature Governance and Parametric Integrity
Consensus: 0.0 temperature established as the absolute rule for private, forensic, and audit environments. For development environments, up to 0.2 is admitted. Temperature up to 0.7 is tolerated only as an exception for qualified interaction; and 1.0 classified as high normative risk.
Regulated Advice Boundaries
Define what can be publicly framed as technical guidance versus institutional/legal interpretation.
How it works
The seven-step route from AI claim to firmed thesis.
The self-regulation workflow adapts the RAG DATA integrity discipline into a governance process: preserve the evidence, open the contradiction, hear the technical debate, and publish only what can be responsibly sustained.
01 / Intake
The AI claim becomes a review record.
The system records what is being questioned, why it matters, who is affected, and which technical or regulatory issue deserves structured review.
Firmed theses
A self-regulation system does not replace institutions. It organizes the debate before escalation.
Delta Cross-Examination is designed as a civic and enterprise layer for responsible AI: it can collect review records, hear technical arguments, document divergence, and publish firmed theses without claiming to replace public authorities, regulators, counsel, or official institutions.
Reusable theses with scope, version, evidence, dissent, and conditions of validity.
Material divergence opens review instead of producing an automatic answer.
The system keeps final legal or regulatory relevance under human supervision.
Public language
Build a public record for AI accountability.
If an AI system affects rights, money, public services, regulated sectors, or professional reliance, its claims deserve more than trust. They deserve a record, a challenge, a response, and a thesis that can be revised when better evidence appears.
Developer environment
Give builders a place to test governance, not only code.
The startup vision includes a developer environment for prompts, evaluation templates, model-role experiments, public issues, audited methods, and controlled challenges. The goal is self-regulation through technical excellence and transparent procedure.
Review topics for debate
Open themes where developers, legal teams, and researchers can challenge AI claims.
Audited methods
Document evaluation procedures, dissent, and limits before a thesis is firmed.
Developer kits
Maintain repeatable forms for intake, evidence, cross-exam, risk, and publication.
Publication area
Normative instructions for model audit and chain of custody.
Delta Cross-Examination now publishes its first normative layer: four safeguards adapted from the registered PrevBot/RAG DATA source, followed by a seven-step append-only audit log for self-regulatory review and certificate-bound SHA-256 linkage.
Publish the debate. Protect the registered method.
The first session consolidated three internal regulations: source protection without code exposure, mandatory human presence in AI auditing, and cryptographic linkage conditioned to an official certificate.
Enterprise contact opened
Enterprise Partnership contact was recorded through the public channel. The Researcher Access submission draft remains pending due to intellectual-property caution.
Temperature Governance and Parametric Integrity
Consensus: 0.0 temperature is the required rule for the absolute majority of critical environments (audit, forensics, and private), with a margin up to 0.2 allowed in development environments. The 0.7 mark is strictly tolerated as an exception for qualified interaction, and 1.0 was classified as normative risk.
Read Public Opinion 002SVG/PDF Viewer
The product track now prioritizes an SVG/PDF metadata viewer with JSON reading, SHA-256 hashes, and custody summaries that non-technical audiences can understand.
Reference without source exposure
A model may enter the audit log to be audited by its applied technical reference. The record must not create a source-code mirror or expose sensitive developer-folder metadata.
Human presence at AI audit
An auditor may be audited by AI only with human oversight. Invocation must generate logs and alert hashes so the event can enter the RAG DATA custody chain.
Certificate-bound SHA-256 linkage
A cryptographic linkage act requires presentation of the official certificate reference before batch hashes, model references, or publication manifests can be treated as custody records.
Official linkage gate
Certificate first. Hash second. Human validation always.
The public record references the registered RAG DATA certificate by controlled identifiers only: INPI BR 51 2026 002804-3, SHA-256 certificate hash, batch manifest hash, model reference hash, and a human gate before any act of cryptographic linkage.
Use the registered program hash as controlled reference, not the raw source.
Require human coordination before model-to-model audit can be treated as record.
Record each event with timestamp, stage, prior hash, and event hash.
Exceptions and similar models require a firmed collegial thesis.
Founding docket
The startup record separates vision, validation, and institutional claims.
The homologation files show a system in formation: collegial decisions, collegial review, cross-provider debate, and a developer-facing governance environment. Provider or institutional participation must remain documented before being stated as endorsement.
Startup thesis
AI self-regulation system
In formation
Coordinator
Miriam Mesquita Reis — Attorney | Specialist in Public and Private Law (EMERJ) | GDPR Certified | Brazilian Bar Association RJ 171.039
Human oversight
Foundation
RAG DATA seven-step integrity discipline
Method base
Thesis journal
Firmed theses, dissent, validity conditions, and revisions
Planned registry
Institutional statements
Require documentary confirmation before publication
Transparency lock
Next public step
Invite review. Preserve the evidence. Respect the institutions.
Origin & Heritage
From the American Adversarial System to Global AI Governance.
Cross-Examination is the fundamental mechanism of the American adversarial legal system, where opposing parties challenge each other's evidence and arguments. This discipline was imported into Brazilian law and is now innovatively applied by Miriam Mesquita Reis to create a structured self-regulation system for AI governance. The Delta Cross-Examination method transposes courtroom adversarial discipline into a technological governance arena.
The adversarial system establishes cross-examination as the primary mechanism for testing evidence and challenging claims under oath.
Brazilian procedural law adopts the cross-examination discipline, integrating it into its legal framework for contradiction and evidence testing.
The registered software method (INPI BR 51 2026 002804-3) formalizes seven-step integrity discipline for AI systems in regulated domains.
Delta Cross-Examination transposes courtroom adversarial discipline into structured AI debate, creating a new paradigm for enterprise AI governance.
Brazilian Bar Compliance
Provimento 205/2021 — Professional Ethics and Public AI Governance.
In Brazil, attorney conduct in digital environments is governed by Provimento 205/2021 of the Federal Council of the Brazilian Bar Association and the Code of Ethics and Discipline (Resolution CFOAB 02/2015). This site constitutes a public debate vehicle and AI governance platform, not attorney advertising. Miriam Mesquita Reis (Brazilian Bar Association RJ 171.039) serves as the human coordinator of the self-regulation method.
Informational content and technical-educational material is permitted under Brazilian bar regulations for digital presence.
Public statements are governance records. They do not commercialize legal services nor substitute professional legal advice.
This platform operates within the boundaries of Brazilian professional ethics, maintaining separation between governance debate and legal practice. ✅ Compliant
Registered Software
RAG DATA Method — INPI BR 51 2026 002804-3.
The method underlying this platform is protected as registered software under Brazilian Law 9.609/98. Public references use only controlled identifiers. Source code is never mirrored, indexed, or exposed on this site.
🔒 Source code protected — Law 9.609/98