Not an AI audit. A structural certainty engagement for enterprises that cannot afford deployment failure. Audit only. No implementation. No conflict of interest. $300K to $400K enterprise tier.
Request Executive Briefing →This is the most important thing to understand about our AI audit practice.
We are independent enterprise architects. Our engagements are strictly limited to diagnostic audits, architectural proofs of concept, and statement of work generation. We do not build production AI workflows. We do not sell implementation retainers. We stress-test your legacy infrastructure, expose operational friction, and write the integration blueprint — then hand it to your internal teams or chosen integrators.
A structured, audit-only engagement producing three distinct deliverables.
A comprehensive evaluation of your organization's readiness for AI integration across three dimensions:
The legal and technical rulebook your organization will use to govern AI implementation. This document arms your procurement and engineering teams with the exact KPIs, security constraints, and performance metrics that integrators must meet before they get paid.
From the Master SOW: The Executing Integrator must design, build, and maintain the AI architecture in strict alignment with ISO/IEC 42001:2023 (global AIMS baseline), including documented risk assessment, data provenance, and continuous monitoring. Where applicable, the system must also adhere to NIST AI RMF 1.0 (Map, Measure, Manage functions), the EU AI Act risk categorization, and the UK AI Regulation Principles (transparency, explainability, human contestability). Failure to meet these architectural guardrails will result in rejection of the deliverable during HAQM IV&V review, and milestone payments will be withheld until compliance is achieved.
In the enterprise world, a proof of concept is not a demo. It is an architectural viability test. We build raw, targeted functional tests to answer one question: will this break?
Can the LLM securely ingest and parse your messy, unstructured legacy data without hallucinating or violating data residency laws?
Can your 20-year-old ERP system handle 500 concurrent AI agent requests without timing out and crashing operational dashboards?
Can we successfully jailbreak the AI using your own proprietary data to validate the vulnerability of proposed guardrails?
Post-SOW oversight that prevents the 95% failure rate. We hold your implementation partners accountable to the binding KPIs and maintenance mandates in your SOW. This is not optional. It is the difference between a deployment that survives contact with operations and one that does not.
This is not a $10,000 vibe audit. This is a comprehensive operational risk mitigation strategy scoped for enterprise complexity.
To ensure depth over breadth, the engagement is constrained to a specific operational perimeter (e.g., North American Supply Chain, or Global Tier-1 Customer Support). Shadow IT and peripheral departments are explicitly excluded from the baseline audit.
Enterprise boards will approve this investment when framed against the cost of a failed AI transformation.
“Right now, your competitors are rushing to implement AI. 95% of enterprise AI projects fail post-deployment because they are sold by vendors who want to build custom tools, not by architects who understand operational reality.
If your board approves a $15 million AI transformation based on vendor hype, and it fails because your legacy APIs can't handle the latency or your data lineage is flawed, that is a career-ending event.
Our engagement is strictly an audit and architectural viability test. We do not build your production workflows. We map operational friction, test the structural limits of your tech stack, and write the binding statement of work. For $400,000, we provide the $15 million insurance policy that ensures when you do pull the trigger on implementation, the architecture will actually survive contact with your daily operations.”
Most AI consultancies are also implementation agencies. This creates a fatal conflict of interest.
No production AI workflows. No prompt engineering retainers. No custom chatbot development. No ongoing implementation services.
Diagnostic audits. Architectural proofs of concept. Vendor governance SOWs. The blueprint and stress-test that ensures implementation success.
Master SOWs with binding KPIs. Vendor oversight frameworks. Technical fiduciaries ensuring integrators build what the business actually needs.
AI does not operate in a vacuum. It operates under intense regulatory scrutiny. The HAQM audit methodology ensures your AI architecture is mapped to global compliance standards before deployment.
We do not rely on vendor promises. We audit your data lineage, API constraints, and fallback protocols against the ISO/IEC 42001 global baseline, the NIST AI RMF (US), the EU AI Act risk tiers, and the UK AI Regulation Principles. If your foundation is brittle or non-compliant, we will not let you build on it.
Whether your data flows through US cloud infrastructure, EU-regulated environments, or UK markets, the HAQM IV&V review verifies that your architecture meets the core mandates of every applicable jurisdiction — before a single line of integration code is written.
Schedule a 30-minute conversation. We will determine whether your enterprise qualifies for this tier of engagement. Not for SMBs seeking chatbots. No commitment.
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