Abstract

Technical Subtitle: From AI Hallucination Prevention and Evidence-Grounded Outputs to Autonomous Agent Security, Synthetic Media Control, Hardware-Verified Authorization, Geospatial Key Release and Protected Execution Finality.

Indian Patent Application No.: 202631051652

Original Filing Date: 23 April 2026

Title as Filed: Systems and Methods for Execution-Time Governance of Machine-Generated Outputs and Actions Using Proof-Gated Semantic Finality and Hardware-Enforced Release Boundaries.

Foundational International Reference: THE DAS PROTOCOLS — International Application PCT/IB2026/055615, filed 4 June 2026.

International Publication: WO 2026/150382 A2 — Published 16 July 2026.

Public Disclosure and Independent Verification: The inventor identifies the 23 April 2026 Indian filing as publicly accessible through the Priority Documents section of the Mothership application PCT/IB2026/055615 on WIPO PATENTSCOPE. Patent examiners, researchers and engineering teams are encouraged to cross-check the original filed specification and claims against the associated international application records.

WIPO Reference: https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2026150382

Industry Relevance: OpenAI · Anthropic · Google DeepMind · Microsoft · Amazon Web Services · NVIDIA · AMD · Intel · Qualcomm · Apple · Meta · Alibaba Cloud · Huawei Cloud · Tencent · Baidu · ByteDance · DeepSeek · Moonshot AI · Zhipu AI · SAP · Mistral AI · OVHcloud · Nokia · Ericsson · Deutsche Telekom · Orange.

Abstract

As artificial intelligence evolves from generating text and images toward executing autonomous workflows, making enterprise decisions, invoking external tools, producing synthetic media and controlling digital infrastructure, a fundamental safety challenge emerges: an AI system's ability to generate an output does not establish that the output is factually grounded, authorized or safe to make externally effective.

The challenge is relevant to global AI ecosystems, including OpenAI's GPT models and Agents SDK, Anthropic's Claude and tool-use infrastructure, Microsoft's Copilot and Foundry Agent Service, Google's Gemini Enterprise Agent Platform and Model Armor, and Amazon Bedrock AgentCore Policy and Gateway. These platforms illustrate environments in which AI-generated responses, tool calls, retrieved evidence and consequential actions may be evaluated before they reach external systems.

Comparable engineering opportunities arise across Alibaba Cloud's Qwen and Model Studio, Huawei Cloud's Pangu and AgentArts, Tencent's Hunyuan and AI agent infrastructure, Baidu's ERNIE and Qianfan, ByteDance's Doubao and Volcano Engine, SAP's Joule and Joule Studio, Mistral AI's Studio platform, and European sovereign-cloud services such as OVHcloud AI Endpoints.

This technical disclosure, based on Indian Patent Application No. 202631051652, filed 23 April 2026, presents an execution-time semantic governance architecture in which machine-generated outputs and actions remain in a non-final, non-externally-effective state until specified evidence, integrity, authorization and release conditions have been independently validated.

The disclosed architecture introduces an Execution-Time Semantic Firewall (ETSF) and Semantic Finality Protocol (SFP) that separate the generation of candidate outputs from authorization to release them. Rather than treating a fluent response, model confidence score, safety-classifier decision or post-hoc citation as sufficient authority, the system generates a structured Proof of Grounding and Integrity (PoGI) bound to the specific candidate artifact.

The PoGI architecture decomposes machine-generated outputs into grounding units, including factual assertions, references, numerical statements, recommendations, action parameters and structured instructions. These units are associated with authenticated evidence sources, content-addressed evidence identifiers, claim-evidence relationships and applicable policy predicates. Evidence-set commitments, including Merkle-based structures in certain embodiments, enable verification that the release decision corresponds to the particular artifact and evidence evaluated.

A Protected Enforcement Domain (PED), implemented through a Trusted Execution Environment, hardware security module, secure coprocessor or equivalent protected mechanism, evaluates the proof object against applicable semantic-integrity, grounding, consistency, policy, purpose and authorization conditions.

Only after successful validation does the protected domain issue a cryptographically authenticated Release Capability bound to the candidate output and relevant execution context. A mandatory Emission Gate verifies that capability before allowing display, API dispatch, network transmission, workflow commitment, data release or other externally consequential effects.

If required verification fails, the architecture enforces a fail-closed Null-Exit condition, withholding external release or producing only a bounded non-execution response.

Additional disclosed embodiments extend proof-gated semantic finality into a broader Sovereign Execution Architecture (SEA), incorporating four complementary dimensions of protected verification:

  • Contextual integrity: Geospatial Cryptographic Key Release (GCKR), trusted location attestations, jurisdiction constraints and temporal authorization.

  • Authorial integrity: Synthetic Identity Actuation Lock (SIAL), privacy-preserving Virtual Identity (VI) mechanisms and contemporaneous human-linked authorization or liveness continuity for selected high-consequence operations.

  • Semantic integrity: Proof of Grounding and Integrity, deterministic policy validation, contradiction checking, approved action primitives and bounded evidence verification.

  • Structural integrity: Runtime model-integrity monitoring, protected execution measurements, approved configuration checks and detection of unauthorized execution changes.

The filing further describes a Universal Agentic Liability Ledger (UALL) for tamper-evident accountability records, recursive proof lineage across cooperating AI agents, protected streaming-output controls, and release authorization tied to verified execution context.

In additional synthetic-media embodiments, candidate images, audio, video and live generated media may be held within protected buffers until required provenance, subject authorization, semantic and jurisdictional predicates are satisfied. Hardware-recognized release boundaries, including secure display pathways, SmartNICs, DPUs and FPGA-based controls in applicable implementations, can condition transmission or rendering on the continued validity of release authorization.

These mechanisms are potentially relevant to NVIDIA BlueField DPUs and confidential computing infrastructure, AMD SEV-SNP, Intel confidential computing, Qualcomm secure computing, enterprise AI gateways, sovereign cloud platforms, AI-native telecommunications, and regulated industrial automation.

The architecture is not intended to replace existing foundation models, safety training, retrieval-augmented generation, enterprise guardrails or cloud security systems. Its proposed additional function is to make external effectiveness conditional on protected verification, especially in environments where an unsupported claim, unauthorized tool invocation, manipulated instruction or synthetic-media release could produce consequential outcomes.

Importantly, cryptographic proof binding does not independently establish objective truth: its effectiveness depends on trustworthy evidence sources, correct semantic verification, complete mediation of relevant output paths and suitable implementation of the protected enforcement boundary. Latency, scalability, bypass resistance and reliability require independent prototype testing.

The central technical contribution is the proposed separation of AI generation from authority to act: a machine may produce a candidate answer, decision or action, but it cannot obtain an authorized external effect within the enforced architecture unless the required proof and release conditions are satisfied.

The disclosure may therefore be relevant to future frontier AI safety, enterprise agent security, evidence-grounded AI, synthetic-media governance, sovereign AI infrastructure, banking, telecommunications, industrial systems and other high-consequence autonomous computing environments.

Keywords

AI Hallucination Mitigation; Execution-Time Semantic Firewall (ETSF); Semantic Finality Protocol (SFP); Proof of Grounding and Integrity (PoGI); Evidence-Grounded AI; Claim-to-Evidence Binding; Semantic Integrity Verification; Protected Enforcement Domain (PED); Hardware-Enforced Execution Finality; Non-Bypassable Emission Gate; Cryptographic Release Capability; Candidate Output Isolation; Fail-Closed Null-Exit; AI Agent Security; Autonomous Agent Governance; Trusted Execution Environment; Confidential Computing; Hardware Security Module; Merkle Proof; Evidence Provenance; Deterministic Action Primitives; Geospatial Cryptographic Key Release (GCKR); Attested Location Packet (ALP); Synthetic Identity Actuation Lock (SIAL); Virtual Identity (VI); Compliance Jurisdiction Token (CJT); Sovereign Execution Architecture (SEA); Universal Agentic Liability Ledger (UALL); Runtime Model Integrity; Synthetic Media Provenance; Deepfake Release Control; Secure Streaming; Zero Trust AI; Critical Infrastructure AI Security.

Technical Alignment and Non-Infringement Disclaimer

Company, platform and product names are included solely to identify possible technical relevance, architectural integration environments and areas for future research. Their inclusion does not indicate that any organization uses, endorses, has adopted, has licensed or infringes the disclosed invention. Product applicability and implementation feasibility require independent technical analysis.

Inventorship and AI-Assistance Statement

The underlying invention is human-originated. AI assistance was used to prepare this explanatory title, abstract, keywords and industry-relevance discussion. The original filed specification and claims remain the authoritative technical sources.

Indian Patent Application: 202631051652 — Filed 23 April 2026.

Foundational International Application: PCT/IB2026/055615 — Filed 4 June 2026.

International Publication: WO 2026/150382 A2 — Published 16 July 2026.

Inventor: Sangam Das.

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