INDUSTRY 5

i5 AI Trust & Transparency (i5 AI-BOM)

Introduction

Modern enterprises are increasingly asked not only to adopt AI systems, but also to prove that those systems are safe, transparent, and accountable. Regulators (like the EU AI Act), customers, and procurement teams all expect clear evidence of how AI makes decisions, where its data comes from, and what guardrails keep humans in control.

The AI-BOM Trust & Transparency documents are designed to meet that expectation. They extend the idea of a Software Bill of Materials (SBOM) into the world of orchestration AI: making the system’s models, data sources, governance rules, and security controls visible in a structured and auditable way.

These documents serve two purposes:

  1. Assurance for external stakeholders — A high-level view that can be shared with auditors, buyers, and regulators, showing that the system meets trust and compliance requirements without disclosing sensitive internals.
  2. Operational clarity for internal teams — A detailed record of lineage, provenance, guardrails, and controls, so that engineers, governance officers, and procurement staff know exactly what is in place.

In practice, this means:

  • Buyers can confirm that models and data have proper provenance.
  • Regulators can see how the system aligns with compliance obligations like human oversight, bias audits, and incident response.
  • Procurement and risk teams can verify that security, encryption, and regional residency policies are honored.
  • Operators and business owners can trust that human‑in‑the‑loop governance is active where it matters.

The result is an AI system that is not a “black box” but a well‑documented, auditable platform for live orchestration.

This document highlights model lineage, data provenance, governance, and integration security to support enterprise procurement, EU AI Act compliance, and internal governance processes.

Model Lineage

Verify that only approved models, prompts, and fine-tunes are active in orchestration.

  • Foundation Models: Commercial LLMs (e.g., example_gpt-ops) with signed provenance and version hashes.
  • Fine-Tunes: Domain-specific (e.g., i5-procurement-agent-ft) trained with LoRA adapters on redacted enterprise + synthetic datasets.
  • Prompt Packages: Version-controlled, signed, and audited for consistency.
  • Lineage Records: Every model and artifact has SHA-256 hashes, training dates, and evaluation references.

Data Provenance

Know which data fractions are synthetic vs. proprietary, how PII is treated, and how ambiguous signals are resolved.

  • Synthetic Data (i5-SDG): Scenario-complete, audit-ready, role-based synthetic data for safe testing.
  • Enterprise Data: Proprietary operational data, with PII tokenization and region-pinned residency.
  • Clean Rooms: Partner joint-planning environments with strict “query-only, no egress” controls.
  • Evidence Layer: Arbitration across logs, message buses, and reports, with confidence scoring and human-escalation.

Governance & Human-in-Loop

Clear accountability: humans remain in control where required by law or policy.

  • Agent Roles: Each role has explicit autonomy thresholds (e.g., ProcurementAgent max order $100k).
  • Smart Agreements: Contracts embed SLA, ESG, and carbon caps, enforced at runtime.
  • Escalation Policies: Mandatory human approval for high-value orders or blacklist overrides.
  • Override Logging: All human or machine overrides must include justification + audit trace.

Integration Security

Strong posture for enterprise IT and compliance teams.

  • Identity: Enterprise IdP integration (OIDC, passkeys) + Rego policy enforcement.
  • Confidential Computing: Workloads attested on AMD SEV-SNP / Intel TDX.
  • Encryption: AES-256 at rest, TLS 1.3 in transit.
  • Residency: Data pinned to EU/US regions with deletion and retention policies.
  • Isolation: Per-tenant namespace + row-level security.

Compliance Alignment

Enterprises can map this BOM directly to regulatory articles and internal audit checklists.

  • EU AI Act: Coverage across data governance, risk classification, bias audits, human oversight, and incident response.
  • Internal Policies: Supports procurement requirements for audit readiness, transparency, and vendor assurance.
  • Safety Evaluations: Regular red-team tests, bias audits, and resilience simulations

Minimal Public Example BOM (JSON)

{
  "system_name": "i5 Orchestration (Public Example)",
  "agent_roles": [
    {"role": "ProcurementAgent", "autonomy": "bounded", "human_override": true},
    {"role": "TransportAgent", "autonomy": "bounded", "carbon_constraint": true}
  ],
  "data_controls": {
    "provenance": ["synthetic", "proprietary", "partner_cleanroom"],
    "pii_treatment": ["hashing", "tokenization"],
    "confidence_model": "consensus+human-escalation"
  },
  "governance": {
    "smart_agreements": ["SLA", "CarbonCap"],
    "audit_logging": "enabled",
    "override_protocol": "justification+trace"
  },
  "security": {
    "encryption": "in-transit+at-rest",
    "residency": "EU/US region pinned",
    "attestation": "confidential-compute"
  },
  "compliance": {
    "regulations": ["EU AI Act", "CSRD"],
    "safety_evals": ["bias-audit", "stress-test", "resilience"]
  }
}