Service 01
AI Readiness Assessment
A structured diagnostic for organizations asking whether they are ready to adopt AI safely and effectively. We examine your data, workflows, skills, governance, and risk posture, then translate the findings into a staged, practical adoption plan matched to your capacity.
Who it's for
- Leadership teams weighing their first significant AI investment
- Public-sector teams that must adopt AI accountably
- Organizations under pressure to "do something with AI" without a clear starting point
Problems it solves
- Uncertainty about where AI genuinely adds value versus hype
- Unclear data quality, workflow, and skills gaps blocking adoption
- Risk of costly pilots that never reach production
What you receive
- AI opportunity and risk scan
- Data and workflow maturity review
- Governance gap assessment
- Practical 30/60/90-day action plan
Why it matters for executives: you get a defensible answer to "are we ready?" before budget, reputation, or public trust is committed.
Service 02
AI Governance Review
A structured, independent review of how your organization governs AI: policies, acceptable use, risk classification, privacy, transparency, and accountability controls. The review benchmarks current practice against recognized governance expectations and produces a prioritized roadmap.
Who it's for
- Regulated organizations deploying or scaling AI systems
- Boards and executives who need assurance that AI use is controlled
- Teams preparing for emerging AI regulation and audit expectations
Problems it solves
- AI use spreading faster than policy and oversight
- Unclear accountability when AI-assisted decisions go wrong
- Privacy, transparency, and fairness obligations without operational controls
What you receive
- Policy and acceptable-use review
- Risk classification framework
- Model and use-case inventory support
- Responsible AI governance roadmap
Why it matters for executives: boards remain accountable for AI-assisted decisions whether or not controls exist. The review shows where oversight actually stands and what to fix first.
Service 03
Data Science & AI Technical Audit
An independent technical examination of models, analyses, and data products your organization relies on or is being asked to buy. We test assumptions, metrics, data quality, validation practice, and uncertainty against how the system actually behaves — not how it is described.
Who it's for
- Organizations making consequential decisions on model outputs
- Buyers who need vendor claims independently verified
- Teams whose analytical work must withstand external scrutiny
Problems it solves
- Models trusted on reputation rather than evidence
- Hidden bias, leakage, or validation flaws in analytical pipelines
- Metrics that look strong but don't measure what matters
What you receive
- Data quality and metric review
- Model assumption and validation check
- Bias, leakage, and uncertainty assessment
- Executive-level technical findings memo
Why it matters for executives: decisions built on flawed models fail quietly and expensively. An independent audit tells leadership whether the numbers deserve their confidence.
Service 04
Quantum Technology Advisory
Practical, scientifically grounded guidance on quantum computing, sensing, and communication: what is real today, what is plausible soon, and what it means for your organization. We assess use-case feasibility, vendor claims, and cryptographic exposure without hype in either direction.
Who it's for
- Organizations planning long-lived security and infrastructure investments
- Leadership teams evaluating quantum vendor proposals or partnerships
- Policy and research groups tracking quantum capability honestly
Problems it solves
- Difficulty separating quantum capability from marketing
- Uncertainty about post-quantum cryptography timelines and exposure
- Strategic decisions made without independent scientific review
What you receive
- Quantum-readiness briefing
- Use-case and feasibility assessment
- Vendor-claim review
- Strategic risk and opportunity map
Why it matters for executives: quantum timelines are uncertain, but cryptographic and infrastructure commitments made today are long-lived. Leadership needs a scientific read, not a sales forecast.
Service 05
Executive Advisory
Ongoing, confidential counsel for executives and boards navigating AI and emerging-technology decisions. A standing independent perspective for reviewing proposals, challenging vendor claims, briefing leadership, and keeping strategy aligned with what the technology can actually deliver.
Who it's for
- CEOs, boards, and senior leaders accountable for technology strategy
- Executives without a senior technical voice at the table
- Organizations facing a stream of AI decisions, not a single project
Problems it solves
- Technology decisions made under sales pressure without independent challenge
- Board-level questions about AI risk with no trusted technical answer
- Strategy drift between leadership intent and technical reality
What you receive
- Standing advisory sessions and on-call counsel
- Proposal and vendor-claim reviews
- Board and executive briefings in plain language
- Decision memos with explicit tradeoffs
Why it matters for executives: a standing independent perspective means proposals are challenged before they are signed — not after they fail.
Service 06
Responsible AI Implementation Support
Hands-on support turning governance principles into working practice: implementing controls, documentation, evaluation routines, and human-oversight processes as AI systems move into production. We work alongside your teams so that responsible AI becomes how the organization operates, not a binder on a shelf.
Who it's for
- Organizations moving from AI policy to deployed systems
- Teams that completed a readiness or governance review and need help executing
- Delivery groups asked to meet responsible-AI requirements for the first time
Problems it solves
- Governance frameworks that exist on paper but not in operations
- Missing evaluation, monitoring, and documentation practice for deployed models
- Unclear human-oversight and escalation paths for AI-assisted decisions
What you receive
- Implementation plan mapped to your governance roadmap
- Control, documentation, and evaluation templates in use
- Team training and oversight-process design
- Follow-up reviews as systems reach production
Why it matters for executives: governance that exists only on paper offers no protection when a deployed system misbehaves. Working controls do.
Service 07
Agentic AI Containment Assurance
An independent technical assessment of what a deployed AI agent can reach, change, disclose, authorize, or damage — and whether your organization can observe and stop it in time. We assess the agent together with its tools, permissions, credentials, data, network paths, memory, orchestration, monitoring, and human intervention mechanisms, then challenge those controls under authorized adversarial and failure-mode conditions.
Who it's for
- Organizations moving an AI agent from pilot into production
- Buyers who need a vendor's autonomy and containment claims independently verified
- Security, risk, and public-sector teams accountable for delegated machine authority
Problems it solves
- "Sandboxed," "read-only," and "human-in-the-loop" asserted as design intent rather than demonstrated
- Agents holding credentials, egress paths, or persistence capability beyond their documented role
- Oversight that cannot intervene faster than the agent can create an irreversible consequence
What you receive
- Agent Authority Map and Agentic Exposure Profile
- Maximum Credible Agent Impact rating (A0–A4)
- Intervention Time, Damage Time, and Containment Margin analysis
- Technical containment test report, control gap register, and 90-day remediation roadmap
Why it matters for executives: autonomy is delegated operational authority. The question a board must be able to answer is not "will the agent behave?" but "what happens when it does not, and how fast can we stop it?"
Service 08
Independent AI Evaluation Assurance
An independent assessment of whether the evidence behind an AI performance claim actually proves what it is being used to prove. We assess a claim — not "the model" — across seven dimensions: construct validity, evidence integrity, statistical reliability, production realism, failure characterization, evaluator independence, and the integrity of the evaluation environment itself. Where scope allows, we reproduce key results on sealed evaluation material the vendor has never seen, and re-run them under your actual security, latency, privacy, and approval constraints.
Who it's for
- Organizations selecting a vendor or foundation model on the strength of benchmark evidence
- Public-sector and regulated buyers who need vendor performance claims independently validated before acceptance
- Boards and executives accepting residual risk before a production deployment
Problems it solves
- Three bidders quoting incomparable benchmarks measured under undisclosed conditions
- Scores produced with unrestricted network access, stubbed tools, undisclosed exclusions, and no approval gates
- Aggregate accuracy that conceals rare, silent, irreversible failures — and failure modes nobody tested for
What you receive
- Evaluation Assurance Scorecard across seven dimensions, with graded evidence and no composite score
- Claim Register with a finding and Evaluation Confidence Level (C0–C4) for every material claim
- Production Evaluation Gap analysis, Failure Register, and Maximum Credible Evaluation Failure
- Remediation roadmap and an Executive Assurance Statement suitable for a procurement record
Why it matters for executives: a benchmark result tells you what happened in a test. Before it justifies a contract or a deployment, someone has to establish that the test deserves to be trusted — and a vendor's own evaluation, however detailed, is documentation rather than independent evidence.
Engagements are scoped around usable outputs such as written findings, executive briefings, risk registers, implementation roadmaps, and decision-ready recommendations. Pricing depends on scope, organization size, data sensitivity, and required deliverables. Confidentiality and data-handling expectations are agreed before work begins.
