# LEO Project Status **Project:** LEO — Human-Controlled Institutional Integrity, Provenance, Evidence Review and Anomaly Analysis System **Repository:** BBS Open System **Document role:** Public project status and evaluation-readiness overview **Status:** Active development and controlled public evaluation preparation **Authority model:** Human review required **Production mutation:** Not authorized by this document --- ## 1. Current Position LEO is a human-controlled institutional integrity system designed to support structured evidence review, provenance preservation, evidence-lineage analysis, process characterization, anomaly analysis, and reviewed institutional knowledge. The current architecture is not based on autonomous enforcement, autonomous institutional decision-making, or automatic fraud determination. LEO is designed to assist human reviewers by organizing evidence, deriving reviewable characteristics from that evidence, determining whether those characteristics are eligible to contribute to process signals, proposing process-mode interpretations, preserving anomaly and review context, and maintaining traceable institutional knowledge subject to human confirmation. The current public-evaluation position of LEO should therefore be understood as: * a controlled institutional review architecture; * an evidence- and provenance-centered analysis system; * a human-review support system; * a process-characterization and anomaly-analysis framework; * a reviewed institutional knowledge architecture; * a collection of controlled runtime baselines and public evaluation artifacts; * an evolving system whose production deployment is not authorized merely because individual runtime baselines are complete or frozen. Historical runtime components remain part of the repository's engineering and institutional memory. They are preserved as evidence of earlier implementation stages but do not independently define the current public architectural position of LEO. --- ## 2. Core Architectural Principle LEO operates under a strict distinction between evidence, derived interpretation, machine-generated proposals, and human-confirmed knowledge. The current canonical interpretation pipeline is: ```text SOURCE EVIDENCE -> EVIDENCE-DERIVED CHARACTERISTICS -> SIGNAL ELIGIBILITY -> DETERMINISTIC / STOCHASTIC SIGNAL COUNTS -> PROCESS MODE PROPOSAL -> HUMAN REVIEW ``` This sequence is intentionally controlled. Source evidence is not treated as automatically verified institutional truth. Evidence-derived characteristics are not equivalent to final institutional conclusions. Signal eligibility determines whether a supported characteristic is permitted to contribute positively to a process-mode signal. Signal counts are analytical inputs, not decisions. A Process Mode result is a proposal for human review, not an autonomous institutional determination. Human confirmation, correction, rejection, or escalation remains outside autonomous machine authority. --- ## 3. Evidence, Provenance and Evidence Lineage Evidence handling is a foundational part of the LEO architecture. LEO is designed to preserve the relationship between: 1. source material; 2. extracted or reviewed evidence; 3. evidence-derived characteristics; 4. signal eligibility decisions; 5. resulting deterministic or stochastic signals; 6. process-mode proposals; 7. reviewer actions; 8. reviewed anomaly records; 9. institutional knowledge derived through reviewed processes. The system must preserve provenance and evidence lineage sufficiently to allow a reviewer to determine where a claim, characteristic, signal, proposal, anomaly record, or knowledge record originated. LEO therefore does not treat derived information as detached from its evidentiary origin. Where evidence is unavailable, incomplete, conflicting, or not observed, the architecture must preserve that state rather than silently transform it into support for an opposite conclusion. The current evidence-derived characteristic state model distinguishes states such as: * `SUPPORTED`; * `NOT_SUPPORTED`; * `NOT_OBSERVED`; * `UNKNOWN`; * `CONFLICTING`. Only signal-eligible `SUPPORTED` characteristics may contribute positive deterministic or stochastic signals. `NOT_SUPPORTED`, `NOT_OBSERVED`, `UNKNOWN`, and `CONFLICTING` remain distinct evidence states and must not automatically generate a positive signal or an opposite signal. This distinction is important for institutional review because absence of support is not automatically evidence of the opposite proposition. --- ## 4. Process Mode The Process Mode layer provides a controlled mechanism for characterizing the operational nature of a reviewed process before downstream interpretation. The canonical Process Mode states are: * `DETERMINISTIC_PROCESS` * `STOCHASTIC_PROCESS` * `MIXED_PROCESS` * `UNKNOWN_REQUIRES_REVIEW` These states are intended to help reviewers distinguish processes governed primarily by stable procedural rules from processes involving behavioral variability, discretionary elements, uncertain responses, or combinations of those characteristics. Process Mode does not determine whether conduct is legitimate, fraudulent, compliant, unlawful, correct, or incorrect. It does not replace professional, institutional, legal, financial, compliance, or investigative judgment. The Process Mode layer instead provides structured review context for subsequent anomaly analysis and institutional interpretation. A process-mode proposal remains subject to human review. --- ## 5. Evidence-Derived Characteristics and Signal Eligibility LEO separates evidence interpretation from signal generation. Evidence-derived characteristics describe characteristics supported, unsupported, unobserved, unknown, or conflicting within the reviewed evidence. Signal eligibility is a separate architectural control that determines whether a supported characteristic may contribute to a deterministic or stochastic process signal. This separation prevents the system from treating every extracted or inferred characteristic as an automatic analytical signal. The current Process Mode architecture distinguishes deterministic-signal characteristics from stochastic-signal characteristics. Examples of deterministic-signal characteristics include: * rule stability; * procedural control; * outcome predictability; * repeatability. Examples of stochastic-signal characteristics include: * human discretion; * behavioral variability; * response uncertainty. Characteristics that are retained for review but are not signal-eligible must remain available as evidence-derived information without automatically affecting signal counts. The architecture therefore preserves a controlled distinction between: ```text evidence -> evidence-derived characteristic -> characteristic state -> signal eligibility -> signal contribution ``` This separation is central to preventing unsupported or ambiguous evidence states from being converted into overconfident process classifications. --- ## 6. Human Review Boundary Human review is a mandatory architectural boundary of LEO. LEO may support a reviewer by: * organizing evidence; * preserving provenance; * deriving reviewable characteristics; * determining signal eligibility according to defined rules; * calculating deterministic and stochastic signal counts; * proposing Process Mode; * identifying and structuring anomaly evidence; * retrieving reviewed institutional knowledge; * presenting evidence lineage; * maintaining review history; * supporting controlled comparison against reviewed precedents. LEO does not independently acquire institutional authority merely because it can perform these functions. The system must not autonomously convert analytical output into enforcement action, sanctions, institutional punishment, fraud findings, legal conclusions, or production mutations. Human reviewers remain responsible for authoritative institutional action. --- ## 7. Explicit Governance Boundaries The current LEO architecture is governed by the following boundaries. ### 7.1 No Autonomous Enforcement LEO is not authorized to autonomously enforce institutional outcomes. Analytical results, anomaly findings, process-mode proposals, or reviewed knowledge retrieval must not automatically become sanctions, restrictions, approvals, rejections, suspensions, or other enforcement actions. ### 7.2 No Autonomous Learning LEO does not treat raw documents or unreviewed machine outputs as self-validating institutional knowledge. Documents are evidence. Human-confirmed classifications and reviewed records may become institutional knowledge under controlled governance. Changes to reviewed knowledge require preserved provenance, review context, and correction history. ### 7.3 No Fraud Verdict Authority LEO does not issue authoritative fraud verdicts. Anomalies, inconsistencies, unusual patterns, missing evidence, contradictory records, or elevated review conditions may justify additional human review, but they do not independently establish fraud. ### 7.4 No Legal Verdict Authority LEO does not independently determine legal liability, regulatory violation, legal guilt, or other authoritative legal conclusions. Legal interpretation remains subject to appropriately authorized human and institutional review. ### 7.5 No Production Mutation The presence of a functioning runtime, completed tests, a frozen baseline, or a completed public demonstration does not authorize production mutation. Production deployment and production-changing actions require separate explicit authorization. ### 7.6 No Unsupported Regulatory Claims Public LEO documentation must not claim regulatory compliance merely because the architecture contains governance, provenance, review, security, or audit-oriented mechanisms. In particular, this project status does not assert independently verified compliance with GDPR, the EU AI Act, or any other regulatory framework unless such a claim is separately supported by appropriate reviewed legal and technical evidence. ### 7.7 No Unsupported Global Test Count Historical test results may be preserved as evidence of specific runtime baselines. A historical test count must not be presented as the current global LEO test count unless a current repository-wide test execution has explicitly established that fact. Historical figures therefore remain tied to the runtime or evaluation baseline from which they originated. --- ## 8. Anomaly Library The Anomaly Library is a governed architectural layer for preserving reviewed anomaly knowledge without converting anomaly detection into autonomous accusation, enforcement, or verdict authority. Its purpose is to allow LEO to accumulate institutional memory about anomalies that have already passed through human review. An anomaly record may preserve information such as: * the reviewed process context; * associated source evidence; * provenance references; * evidence-derived characteristics; * Process Mode context; * observed anomaly characteristics; * reviewer interpretation; * correction or resolution history; * recurrence information; * related reviewed examples; * uncertainty or unresolved questions; * subsequent review outcomes. An anomaly is not synonymous with fraud, wrongdoing, illegality, or institutional failure. Anomalies may result from many causes, including: * legitimate procedural variation; * incomplete information; * data-quality problems; * inconsistent documentation; * process deviation; * exceptional circumstances; * human error; * system error; * conflicting evidence; * unexplained behavior requiring additional review. The architectural purpose of the Anomaly Library is therefore not to create an automated blacklist or enforcement mechanism. Instead, it provides controlled institutional memory that can help reviewers understand whether a newly observed condition resembles previously reviewed anomaly patterns and what happened during those earlier reviews. Anomaly knowledge must remain connected to provenance and review history. Historical anomaly records must not be silently rewritten when later evidence changes their interpretation. Corrections should preserve the previous state together with the reason, authority, and evidence supporting the correction. The Anomaly Library is therefore intended to support: ```text reviewed anomaly -> preserved evidence lineage -> human interpretation -> review outcome -> institutional memory -> future reviewer support ``` It is not intended to support: ```text detected anomaly -> automatic accusation -> automatic enforcement ``` --- ## 9. Reviewed and Institutional Knowledge LEO distinguishes evidence from reviewed institutional knowledge. A document, record, message, transaction, report, dataset, external source, or other submitted material may constitute evidence. It does not automatically become institutional knowledge merely because it was ingested or processed by the system. The governing principle is: ```text Documents are evidence. Human-confirmed classifications are knowledge. ``` Reviewed or Institutional Knowledge is created through controlled review, not through autonomous ingestion. A reviewed knowledge record should preserve sufficient context to understand: * what evidence supported it; * which evidence-derived characteristics were relevant; * which Process Mode context applied; * who or what review authority confirmed the record; * when the confirmation occurred; * whether uncertainty remained; * whether later corrections occurred; * which previous version or interpretation it superseded; * which anomaly records or reviewed cases were relevant; * whether the knowledge remains active, superseded, disputed, or under review. This architecture is designed to prevent institutional memory from becoming detached from its source evidence. LEO must also preserve correction history. If reviewed institutional knowledge changes, the previous reviewed state should remain traceable rather than being silently replaced as though it never existed. This allows institutional knowledge to evolve while preserving historical accountability. The Reviewed / Institutional Knowledge layer is therefore intended to support cumulative institutional understanding without presenting machine-generated interpretation as self-validating truth. --- ## 10. Reviewer Support LEO is designed as a reviewer-support system. Its analytical and knowledge capabilities are intended to make complex institutional evidence easier to inspect, compare, trace, and review. Reviewer support may include: * structured presentation of source evidence; * evidence provenance and lineage; * evidence-derived characteristics; * characteristic state; * signal eligibility; * deterministic and stochastic signal counts; * Process Mode proposals; * anomaly context; * reviewed anomaly precedent; * relevant reviewed institutional knowledge; * unresolved evidence conflicts; * missing or unobserved evidence; * historical review context; * correction lineage; * reproducible runtime output where applicable. The purpose of these capabilities is to improve the quality, traceability, and consistency of human review. They are not a mechanism for transferring institutional authority from humans to the system. A reviewer should be able to distinguish: ```text SOURCE FACT DERIVED CHARACTERISTIC SYSTEM-GENERATED SIGNAL SYSTEM PROPOSAL REVIEWED KNOWLEDGE HUMAN DECISION ``` These categories should not be collapsed into a single machine-generated conclusion. Where LEO cannot establish sufficient evidence for a process interpretation, uncertainty should remain visible. `UNKNOWN_REQUIRES_REVIEW` exists precisely because the architecture permits unresolved states instead of forcing every case into a confident classification. --- ## 11. Controlled Runtime Baselines LEO contains multiple runtime components, demonstrations, tests, and previously completed implementation baselines. These artifacts are important engineering evidence. However, a completed runtime baseline does not automatically establish that the entire LEO architecture is production-ready. A controlled runtime baseline demonstrates only the scope that was actually implemented, tested, reviewed, and frozen within that baseline. A current evaluator-facing Process Mode runtime evidence package is available at: [`evaluation/PROCESS_MODE_RUNTIME_EVIDENCE.md`](./evaluation/PROCESS_MODE_RUNTIME_EVIDENCE.md) It provides scoped evidence for the implemented Process Mode path and its review boundaries. Its presence does not change the distinction between implemented runtime behavior, broader architectural development, and production-authorized functionality. A corresponding evaluator-facing Anomaly Library runtime evidence package is available at: [`evaluation/ANOMALY_LIBRARY_RUNTIME_EVIDENCE.md`](./evaluation/ANOMALY_LIBRARY_RUNTIME_EVIDENCE.md) It documents the frozen Anomaly Library runtime baseline, implemented validation and orchestration behavior, test-backed evidence, evidence-lineage and provenance requirements, and the mandatory human-review boundary. Its presence does not constitute production authorization or autonomous institutional authority. A corresponding evaluator-facing Knowledge Layer runtime evidence package is available at: [`KNOWLEDGE_LAYER_RUNTIME_EVIDENCE.md`](./KNOWLEDGE_LAYER_RUNTIME_EVIDENCE.md) It documents the published Knowledge Layer runtime boundary, including controlled knowledge-integration records, reference resolution, evidence-lineage and provenance validation, implementation-contract control, controlled input loading, test-backed behavior, and mandatory human review. Its presence does not constitute production authorization, autonomous institutional authority, or self-validating institutional knowledge. Accordingly, public status documentation must distinguish among: * implemented runtime behavior; * tested runtime behavior; * frozen historical baselines; * architectural specifications; * public demonstrations; * evaluation artifacts; * planned or future architecture; * production-authorized functionality. A component may be technically complete within a defined runtime baseline while the broader system remains under architectural development and public evaluation preparation. Similarly, a runtime may be frozen to preserve reproducibility without being designated for production deployment. The term `frozen` should therefore be interpreted as a preservation and change-control state, not as automatic production authorization. Runtime evidence should remain reproducible where practical and should preserve the relationship among: ```text input -> processing -> output -> validation -> review ``` This allows public evaluators and internal reviewers to distinguish demonstrated system behavior from architectural claims that have not yet been implemented. --- ## 12. Historical Test Evidence Historical test results remain part of the project evidence base. They should be preserved with the scope and runtime context in which they were obtained. For example, a previously recorded result of: ```text 2451 passed in 56.87s ``` belongs to a historical Institutional Approval combined runtime baseline. It should not be interpreted or published as a current global LEO test count without a new, explicitly scoped repository-wide validation establishing that claim. The correct public interpretation is therefore: * historical test results may demonstrate the validated state of a specific runtime baseline; * historical results remain useful reproducibility evidence; * they do not automatically describe the current entire repository; * they must remain attached to their original test scope; * new global claims require new global evidence. This distinction prevents historical engineering evidence from being transformed into unsupported current-state metrics. --- ## 13. Legacy Runtime Components Earlier LEO implementation stages included runtime components and terminology associated with case escalation, risk escalation, institutional alerts, automatic case triggers, and related processing. Examples preserved in the repository include historical components such as: * `RiskEscalationEngine`; * `CaseEscalationEngine`; * `InstitutionalAlertEngine`; * `CaseEngine`; * `AutomaticCaseTrigger`. These components constitute historical implementation evidence. Their presence is important to engineering provenance and institutional memory. They should not be deleted or rewritten merely because the current architecture has evolved. At the same time, their historical existence must not be used to imply that autonomous escalation or enforcement represents the current governing architecture of LEO. Current public positioning is governed by the present architecture and its explicit human-review boundaries. Legacy runtime components therefore belong to a historical evidence category: ```text LEGACY / HISTORICAL RUNTIME EVIDENCE ``` rather than automatically defining: ```text CURRENT PUBLIC ARCHITECTURAL AUTHORITY ``` Where historical terminology conflicts with current architectural terminology, current public documentation should explain the distinction rather than silently rewriting historical artifacts. This preserves both architectural continuity and provenance. --- ## 14. Historical Terminology Earlier public or runtime documentation may contain terminology developed under previous architectural phases. Terms such as: * structured truth ingestion; * risk escalation mechanisms; * institutional alert pipeline; * automatic triggering; * pilot readiness; must be interpreted in their historical context. They should not automatically be projected onto the current LEO architecture. In particular, `structured truth ingestion` is no longer an appropriate top-level description of the present evidence model. The current architecture deliberately distinguishes: ```text evidence from reviewed knowledge ``` and does not assume that ingested material is institutional truth. Similarly, risk escalation and institutional alert terminology must not imply current autonomous enforcement authority. Where legacy mechanisms remain in runtime history, they remain preserved as historical evidence unless separately reviewed and incorporated into a current governed architecture. --- ## 15. Public Evaluation Readiness The current strategic direction of LEO includes public visibility and public evaluation readiness. Public evaluation readiness is not equivalent to a claim that every planned LEO capability has been implemented or that the system is production-ready. It means that the project is being organized so an external evaluator can increasingly determine: * what LEO is; * what LEO is not; * which architectural principles govern it; * which functionality is implemented; * which functionality is historical; * which runtime demonstrations can be reproduced; * which claims are supported by evidence; * how evidence lineage is preserved; * how human review is maintained; * where architectural boundaries exist; * which areas remain under development; * which areas require further validation. A useful public evaluation package should allow evaluators to follow a coherent path from project overview to architecture, demonstrations, evidence, validation, and governance boundaries. Public evaluation documentation should therefore favor traceability over marketing claims. Claims should be proportionate to available evidence. Where capability has not been demonstrated, it should not be presented as demonstrated. Where architecture is defined but implementation remains incomplete, that distinction should be visible. Where a baseline is historical, its date and scope should remain identifiable. Where a question remains unresolved, public documentation should permit the unresolved state to remain visible. --- ## 16. Public Evaluation Does Not Equal Production Authorization Public evaluation and production deployment are separate governance states. A repository may be publicly inspectable. A demonstration may be reproducible. A runtime baseline may be complete. Tests may pass within their defined scope. Architecture may have passed internal continuity review. None of these conditions independently authorizes production deployment. Production authorization requires an explicit decision under the applicable governance, security, operational, legal, and institutional controls. The current public status should therefore not imply that LEO is authorized to mutate live institutional systems or independently execute consequential decisions. The distinction is: ```text PUBLICLY EVALUABLE != PRODUCTION AUTHORIZED ``` and: ```text RUNTIME COMPLETE != AUTONOMOUS AUTHORITY ``` --- ## 17. Institutional Memory and Historical Preservation LEO treats historical evidence as part of system memory. Architectural development should not create the appearance that prior states never existed. Historical documentation, runtime baselines, review decisions, anomaly records, correction records, and previous architectural models may all provide useful provenance. Accordingly, architectural evolution should generally use: * explicit supersession; * status labeling; * correction history; * provenance references; * archived evidence; * review records; rather than silent historical deletion. This principle applies both to institutional knowledge handled by LEO and to LEO's own engineering history. Preserving history allows future reviewers to understand: * what the system previously did; * why an architectural change occurred; * what evidence informed the change; * which previous assumptions were rejected or refined; * which behavior remains historical only; * which current rules supersede earlier approaches. Institutional memory therefore forms part of LEO's integrity model rather than being treated merely as obsolete repository material. --- ## 18. Current Capability Model The current LEO capability model should be interpreted as a set of governed architectural and runtime layers rather than as a single autonomous decision engine. At a high level, the system is developing around the following relationship: ```text SOURCE EVIDENCE -> EVIDENCE / PROVENANCE HANDLING -> EVIDENCE-DERIVED CHARACTERISTICS -> SIGNAL ELIGIBILITY -> PROCESS MODE -> ANOMALY ANALYSIS -> REVIEWED / INSTITUTIONAL KNOWLEDGE -> REVIEWER SUPPORT -> HUMAN REVIEW ``` These layers do not all represent the same implementation maturity. Some capabilities exist as controlled runtime baselines. Some exist as reviewed architectural contracts and specifications. Some are represented by public demonstrations or evaluation artifacts. Some remain under continued development. Public documentation should preserve these distinctions rather than presenting the architecture as a uniformly completed production system. --- ## 19. Process Mode as Context for Anomaly Analysis Process Mode is an important contextual layer for anomaly interpretation. The same observation may have different significance depending on whether the underlying process is primarily deterministic, stochastic, mixed, or insufficiently characterized. For example, variation in a tightly controlled deterministic workflow may justify a different review question than similar variation in a process where human discretion and behavioral variability are expected. The purpose of Process Mode is therefore not merely classification for its own sake. It provides structured context for downstream review. The intended architectural relationship is: ```text PROCESS CHARACTERIZATION -> ANOMALY CONTEXT -> REVIEWED INTERPRETATION ``` rather than: ```text ANOMALY -> AUTOMATIC VERDICT ``` This distinction is fundamental to the current LEO architecture. No anomaly-learning or anomaly-comparison mechanism should bypass the process context, evidence lineage, or human-review boundary required by the governed architecture. --- ## 20. Knowledge Accumulation Model LEO is intended to accumulate institutional memory gradually through reviewed evidence and human-confirmed interpretation. The system is not intended to autonomously learn institutional truth from raw documents. The knowledge accumulation model is instead based on reviewed progression: ```text SOURCE EVIDENCE -> REVIEWABLE INTERPRETATION -> HUMAN REVIEW -> CONFIRMED / CORRECTED / REJECTED RESULT -> PRESERVED REVIEW RECORD -> REVIEWED INSTITUTIONAL KNOWLEDGE ``` Future use of that knowledge must retain access to its provenance and review history. Where later evidence changes an earlier interpretation, the architecture should support correction without destroying the historical record. This creates a reversible and auditable knowledge lineage rather than an opaque machine-memory state. Institutional knowledge should therefore be capable of representing uncertainty, supersession, correction, and disagreement where those states are material to later review. --- ## 21. Architecture and Runtime Must Remain Distinguishable LEO documentation must distinguish architectural intent from demonstrated runtime behavior. An architectural contract may define required behavior before a complete runtime implementation exists. A runtime implementation may demonstrate a subset of the architecture. A historical runtime may implement behavior that has since been superseded architecturally. A public demonstration may intentionally exercise only a constrained evaluation path. These states should not be conflated. Public claims should therefore answer, where relevant: * Is this an architectural requirement? * Is this implemented? * Is this tested? * Is this demonstrated publicly? * Is this historical? * Is this frozen for reproducibility? * Is this under active development? * Is this production-authorized? This distinction is particularly important as LEO evolves from isolated runtime demonstrations toward a more integrated institutional integrity architecture. --- ## 22. Controlled Demonstrations Public LEO demonstrations are intended to provide inspectable evidence of defined capabilities. A demonstration should not be interpreted as proof of capabilities outside its documented scope. A controlled demonstration may provide evidence for: * structured input handling; * evidence review; * provenance preservation; * evidence-lineage construction; * process characterization; * anomaly presentation; * reviewer-facing output; * reproducible execution; * validation of a specific runtime path. The presence of a demonstration does not establish autonomous institutional authority. A demonstration also does not establish production deployment readiness unless production readiness has been separately evaluated and explicitly authorized. Public demonstrations should therefore remain narrow enough that evaluators can understand what was actually exercised and reproduce the relevant behavior where the repository provides the required artifacts. --- ## 23. Current Development State LEO remains under active architectural and engineering development. The project has progressed beyond its earlier public description and now includes a broader governance-centered architecture involving: * evidence and provenance handling; * evidence-derived characteristics; * signal eligibility; * Process Mode; * anomaly analysis and reviewed anomaly memory; * Reviewed / Institutional Knowledge; * human-review support; * controlled runtime baselines; * public evaluation infrastructure; * architectural continuity and provenance preservation. This development state should not be represented using a single legacy phase label if that label no longer accurately describes the current architecture. Earlier phase and pilot-readiness terminology may remain historically useful, but current public status should be based on the capabilities, governance boundaries, evidence, and evaluation artifacts that actually exist. The project is therefore better characterized as being in: ```text ACTIVE ARCHITECTURAL AND ENGINEERING DEVELOPMENT + CONTROLLED PUBLIC EVALUATION PREPARATION ``` rather than as a completed autonomous institutional platform. --- ## 24. Current Public Evaluation Priorities The current public-evaluation work focuses on making the repository understandable and reviewable without overstating system maturity. Priority areas include: 1. architectural clarity; 2. evidence and provenance traceability; 3. evidence-lineage visibility; 4. clear separation of historical and current architecture; 5. reproducible runtime evidence; 6. accurate capability descriptions; 7. explicit governance boundaries; 8. human-review visibility; 9. consistency across public documentation; 10. preservation of institutional and engineering memory. Public documentation alignment is part of this work. The objective is not to erase the historical repository state. The objective is to ensure that the public entry path accurately explains how current LEO architecture relates to historical implementation evidence. --- ## 25. Known Limitations and Boundaries LEO should be evaluated with explicit awareness of its current limitations and governance boundaries. ### 25.1 Architecture Is Broader Than Any Single Demo No individual public demonstration should be interpreted as representing the complete LEO architecture. ### 25.2 Runtime Baselines Have Defined Scope A runtime baseline establishes evidence only for the behavior and validation actually included in that baseline. ### 25.3 Historical Components Remain Present Legacy runtime components and terminology remain in the repository for provenance and institutional-memory reasons. Their presence does not automatically represent current architectural authority. ### 25.4 Human Review Remains Required Machine-generated characteristics, signals, Process Mode proposals, anomaly structures, and retrieved knowledge do not replace authoritative human review. ### 25.5 No Autonomous Institutional Enforcement LEO is not currently authorized as an autonomous enforcement mechanism. ### 25.6 No Fraud or Legal Verdict Authority LEO anomaly analysis does not constitute an authoritative fraud finding, legal judgment, or regulatory determination. ### 25.7 No Production Mutation Authority Public evaluation artifacts, completed runtime baselines, or passing tests do not independently authorize mutation of production systems. ### 25.8 Regulatory Compliance Is Not Claimed Without Evidence Architecture designed around provenance, human review, traceability, and controlled authority should not be represented as proof of regulatory compliance. Any future GDPR, EU AI Act, sector-specific, contractual, or other regulatory compliance claim requires separate appropriate review and supporting evidence. ### 25.9 Global Test Status Requires Current Global Evidence Historical test results remain valid historical evidence within their documented scope. They must not be transformed into a current global test-count claim without a current appropriately scoped validation. --- ## 26. Evaluation Guidance An evaluator reviewing LEO should distinguish between four categories of repository material. ### 26.1 Current Governing Architecture These materials define the current architectural model, terminology, governance boundaries, and intended relationships among evidence, signals, Process Mode, anomalies, reviewed knowledge, and human review. ### 26.2 Current Runtime Evidence These materials demonstrate currently preserved runtime behavior within a defined scope. ### 26.3 Public Evaluation Artifacts These materials are organized specifically to help an external evaluator understand, execute, inspect, or validate selected LEO capabilities. ### 26.4 Historical / Legacy Evidence These materials preserve earlier runtime implementations, terminology, design assumptions, or project phases. Historical evidence remains relevant to provenance but should not automatically override the current governing architecture. When apparent contradictions occur, evaluators should first determine whether the compared artifacts belong to different architectural periods or evidence categories. Historical preservation is intentional. --- ## 27. Claim Discipline Public LEO documentation follows an evidence-based claim discipline. A public statement should not exceed the evidence available to support it. This means: ```text IMPLEMENTED ``` should describe functionality that exists in implementation. ```text TESTED ``` should describe functionality supported by appropriately scoped test evidence. ```text DEMONSTRATED ``` should describe functionality exercised by an inspectable demonstration. ```text ARCHITECTURALLY DEFINED ``` should describe behavior established by reviewed architecture but not necessarily fully implemented. ```text HISTORICAL ``` should describe evidence preserved from an earlier system state. ```text PLANNED ``` or equivalent language should be used where functionality remains future work. These categories should not be substituted for one another merely to simplify public messaging. This discipline is intended to make public evaluation more reliable and to reduce ambiguity about what LEO currently demonstrates. --- ## 28. Security, Governance and Institutional Authority LEO's architecture assumes that technical capability and institutional authority are different concepts. A system may technically be capable of generating a classification, alert, recommendation, or structured output without possessing institutional authority to act on it. Institutional authority must be governed separately. Accordingly, LEO architecture should preserve boundaries among: ```text ANALYSIS RECOMMENDATION / PROPOSAL HUMAN REVIEW AUTHORIZATION INSTITUTIONAL ACTION ``` The existence of upstream analytical capability does not automatically authorize downstream institutional action. This separation is required for a human-controlled integrity system. --- ## 29. Licensing and Intellectual Property Review Gate Public documentation alignment does not itself resolve licensing, intellectual-property, or third-party dependency questions. Before broader publication, institutional collaboration, corporate cooperation, developer participation, foundation cooperation, or EU/institutional engagement is treated as publication-ready, the repository's licensing position requires a dedicated consistency review. That review should address the relevant licensing and intellectual-property artifacts separately from this project-status alignment. The review should determine, based on repository evidence, whether public-facing licensing statements, repository licensing artifacts, third-party components, dependency licensing, contribution expectations, and intellectual-property positioning are mutually consistent. This document does not pre-judge the result of that review. No licensing or regulatory conclusion should be inferred merely from the existence of licensing-related files in the repository. The dedicated licensing review remains a separate publication-readiness gate. --- ## 30. Publication-Readiness Sequence The current public documentation alignment should proceed in a controlled sequence. The intended sequence is: ```text PROJECT_STATUS.md -> README.md -> PUBLIC_DEMO_CATALOG.md -> index.html -> CROSS-DOCUMENT ARCHITECTURAL CONTINUITY / CONSISTENCY REVIEW -> LICENSE / IP / THIRD-PARTY LICENSING CONSISTENCY REVIEW -> FINAL PUBLICATION-READINESS REVIEW -> EXPLICIT HUMAN APPROVAL -> PUBLIC REPOSITORY UPDATE -> FRESH-CLONE / POST-PUSH VERIFICATION ``` Completion of an earlier step does not authorize skipping later review gates. In particular, completion of public documentation alignment does not authorize publication before the licensing and final publication-readiness gates have been addressed. --- ## 31. Public Status Declaration The current LEO public status is: **ACTIVE ARCHITECTURAL AND ENGINEERING DEVELOPMENT** **CONTROLLED PUBLIC EVALUATION PREPARATION** **HUMAN REVIEW REQUIRED** LEO is being developed as a human-controlled institutional integrity, provenance, evidence review, process characterization, anomaly analysis, and reviewed knowledge system. Its current architecture preserves the distinction between source evidence, evidence-derived characteristics, signal eligibility, analytical signals, Process Mode proposals, reviewed anomalies, institutional knowledge, and authoritative human decisions. Historical runtime components remain preserved as engineering and institutional evidence. They do not automatically define current architectural authority. Controlled runtime baselines and public demonstrations provide evidence within their documented scopes. They do not independently establish complete-system production readiness. LEO does not claim autonomous enforcement authority. LEO does not claim autonomous learning authority over institutional truth. LEO does not issue authoritative fraud verdicts. LEO does not independently issue authoritative legal verdicts. LEO is not authorized by this status document to mutate production systems. No current global LEO test count is asserted here without current appropriately scoped validation. No GDPR, EU AI Act, or other regulatory compliance claim is asserted here without separate appropriate evidence and review. Production deployment requires separate explicit authorization. Licensing, intellectual-property, and third-party licensing consistency remain subject to a dedicated review gate before final publication readiness. --- ## 32. Architectural Continuity Statement The current public position of LEO does not require deletion or concealment of earlier engineering history. Legacy runtime components, previous terminology, historical demonstrations, historical test baselines, and earlier architectural stages remain part of the project's provenance. Current architecture supersedes earlier public positioning where the two differ, but historical evidence should remain identifiable and reviewable. The governing continuity principle is: ```text PRESERVE HISTORY + IDENTIFY CURRENT AUTHORITY + PRESERVE PROVENANCE + MAKE SUPERSESSION EXPLICIT + REQUIRE HUMAN REVIEW ``` This approach allows LEO to evolve without losing the evidence required to understand how and why the system changed. --- ## 33. Current Review Decision The previous public project-status positioning no longer adequately represents the current LEO architecture. A public status centered on structured truth ingestion, risk escalation, institutional alert pipelines, legacy phase positioning, or unsupported current test-count claims would create a material mismatch between the public description and the current governed architecture. The replacement status should instead center on: * source evidence; * provenance; * evidence lineage; * evidence-derived characteristics; * signal eligibility; * Process Mode; * anomaly analysis; * reviewed anomaly memory; * Reviewed / Institutional Knowledge; * reviewer support; * human review; * controlled runtime evidence; * historical preservation; * explicit governance boundaries; * controlled public evaluation. **Review decision: PUBLIC PROJECT STATUS REALIGNMENT REQUIRED.** The purpose of this realignment is architectural accuracy and continuity, not removal of historical evidence. --- ## 34. Next Controlled Public-Documentation Step After this `PROJECT_STATUS.md` replacement has been reviewed, explicitly approved, applied to the correct public-repository source, and verified, the next documentation-alignment target is: ```text README.md ``` No automatic modification of `README.md`, `PUBLIC_DEMO_CATALOG.md`, `index.html`, licensing artifacts, runtime components, historical evidence, or other repository files is authorized by this document. Each subsequent change remains subject to separate controlled review and explicit human approval.