You need a defensible answer.
The board, customers, audit, or regulators will ask how AI is governed. A policy deck is not enough. Buyers need evidence, ownership, and a visible plan.
RAXE Advisory Services
Evidence-led · AI-native · Response-oriented
If your board asked about AI risk tomorrow, would you answer with evidence or opinion?
AI usage is moving faster than control. Production systems are live before they are properly tested. Incident ownership is unclear. Leadership needs a defensible answer now. RAXE turns that uncertainty into evidence, priority, and an action register people can actually execute.
Why buyers move
Four pressures we hear before every engagement.
Board, production, incident, or scale — the trigger is rarely curiosity. The service is the mechanism; the real product is clarity, readiness, and faster executive decisions.
Your AI is live, but not properly tested.
Traditional security testing can say the app is clean while the agent still has dangerous paths, unsafe tool access, or prompt-driven behaviour nobody has validated.
Your team has never handled an AI incident.
When ownership is unclear, the first hour becomes expensive. Buyers want to pressure-test the decision chain before legal, comms, security, and engineering are improvising.
You are spending on AI without knowing what should scale.
Pilots multiply, spend rises, and leadership still cannot tell where the next budget pound or dollar should go. Buyers want a maturity view tied to action.
Problem-first entry points
Pick the problem that best describes your Monday morning.
Each starting point is written around the pressure the buyer is trying to remove. The service is the mechanism. The outcome is clarity, readiness, and faster executive decisions.
Services at a glance
- AISPA Security posture baseline 2–4 weeks Evidence register + 30/90/180/365-day roadmap
- AI-TTX Incident readiness exercise 1–2 weeks + workshop After-action report + action register
- AI-RTA Adversarial testing 2–3 weeks Findings report + remediation plan
- AIMA Adoption maturity review 3–5 weeks 7-dimension scorecard + investment priorities
- Retainer Ongoing advisory Quarterly cadence Live action tracker + executive readout
Why buyers move
Because the next board, audit, customer, or regulator question cannot be answered with a policy PDF and good intentions.
What happens if you wait
Every new AI decision stays anecdotal. Blind spots grow. Future incidents, reviews, and investments all start from guesswork.
What changes after
You get an evidence-backed baseline, framework mapping, ownership, and a prioritised 30 / 90 / 180 / 365 day action register.
Pressure removed
No more vague answers.
The conversation shifts from “we think we are fine” to “here is what exists, what is exposed, and what needs fixing first”.
Board-ready baseline
What buyers are really buying
Evidence, not reassurance.
An executive view leadership can defend, and a level of detail security and engineering can actually work from.
8 domains · evidence-led
Best fit
Use this when AI is already spreading.
Especially when business units, product teams, or shadow AI usage are outpacing security visibility.
Good first move
Executive summary
Scorecard
Evidence register
Roadmap
Scope this engagement
Why buyers move
Because no one wants legal, comms, engineering, and the executive team improvising around an AI incident at production speed.
What happens if you wait
The first real inject becomes the rehearsal. Ownership gets blurred. Response time stretches. Messaging fractures.
What changes after
You know who owns the first hour, where escalation breaks, which gaps matter most, and what needs fixing before the real incident.
Pressure removed
No more fuzzy ownership.
The exercise exposes who actually decides, escalates, communicates, and recovers when AI-specific events hit.
Practised chain
What buyers are really buying
Confidence under pressure.
Not a workshop for its own sake. A faster, clearer decision chain with named owners and target dates.
Readiness scoring
Best fit
Use this when AI incidents would go cross-functional immediately.
Especially where customer impact, leadership visibility, or reputational risk would appear in hours, not days.
First-hour clarity
Scenario pack
Observation matrix
After-action report
Action register
Scope this engagement
Why buyers move
Because production AI creates attack paths that SAST, DAST, and standard web testing can miss completely.
What happens if you wait
Tool abuse, prompt injection, unsafe agency, and RAG poisoning remain theoretical until an attacker or researcher proves otherwise.
What changes after
You get reproducible evidence, severity, mapped findings, and a remediation plan that engineering can action quickly.
Pressure removed
No more false comfort from legacy testing.
You see what an attacker can really do, not just what a generic checklist was built to inspect.
AI-specific attack surface
What buyers are really buying
Proof, severity, and fix priority.
The value is not “a red team”. It is fast, reproducible evidence that lets the business harden the right thing first.
ATLAS + OWASP mapped
Best fit
Use this when AI is customer-facing or operationally critical.
Especially where agents, RAG, tool calling, MCP, or model-serving exposure create new routes to impact.
72-hour fix mindset
Rules of engagement
Findings report
Reproduction steps
Remediation plan
Scope this engagement
Why buyers move
Because leadership needs to know where to invest next, which departments can scale, and what is still blocking value.
What happens if you wait
Budget keeps spreading across pilots, maturity stays uneven, and the board still cannot see where the next quarter should go.
What changes after
You get a maturity view across strategy, data, technology, talent, governance, security, and operations, plus a transformation roadmap.
Pressure removed
No more broad AI optimism without a readiness signal.
The assessment separates departments that can scale from teams that still need foundational work.
Scale signal
What buyers are really buying
Prioritised investment decisions.
It is less about a maturity score and more about where the next pound, dollar, or quarter of effort should land.
7 dimensions
Best fit
Use this when leadership wants scale, not more pilots.
Especially when AI ambition is rising but the operating model, controls, and foundations are not aligned.
Transformation roadmap
Executive summary
Dimension scorecard
Heatmap
Investment priorities
Scope this engagement
Why buyers move
Because AI usage changes monthly, new vendors appear fast, and static findings go stale unless someone keeps the register moving.
What happens if you wait
The action register quietly dies, controls drift away from reality, and leadership only gets an update when something breaks.
What changes after
You get a live rhythm: advisory sessions, risk reviews, control tuning, and recurring executive readouts that keep momentum visible.
Pressure removed
No more roadmap decay.
The retainer stops assessments from becoming static documents that nobody reopens after quarter close.
Monthly cadence
What buyers are really buying
Continuity and executive visibility.
The value is not “advice on call”. It is making sure progress, risk, and priorities stay live as AI usage changes.
Quarterly readout
Best fit
Use this when the first move is already done.
Especially after an assessment, tabletop, or red team when leadership wants visible follow-through rather than another thick report.
Keeps momentum alive
Action tracker
Risk register
Control tuning
Executive readout
Scope this engagement
What buyers walk away with
The output is not just a report. It is a faster decision environment.
Answers, ownership, proof, and a next-move list leadership can actually act on.
01
A board-ready narrative
A concise answer leadership can actually use: what is happening, what is exposed, what matters most, and what should happen next.
02
An evidence register
Every major point can be traced back to interviews, artefacts, configurations, telemetry, or tested behaviour.
03
A prioritised action register
Not generic recommendations. A sequenced view of what gets fixed first, what waits, and why.
04
Named owners and dates
Useful work needs accountability. Buyers are paying for movement, not more observations.
05
Framework-aligned structure
NIST AI RMF, OWASP, ATLAS, ISO/IEC 42001 readiness concepts, and operational gap references where useful.
06
A clearer control path
Where relevant, findings can map into RAXE Gateway, SDK, or Host Sensor — but risk, evidence, and action come first.
Recommended sequences
Most buyers do not need every service. They need the right first move.
Four common starting paths, based on the pressure in front of you today.
Visibility path
We do not know where AI is being used or how exposed we are.
Start with posture, then test incident readiness, then keep the roadmap alive.
AISPA
AI-TTX
Retainer
Readiness path
The board wants to know if we could handle an AI incident.
Start with the exercise, fix the chain, then baseline the rest of the posture.
AI-TTX
AISPA
Retainer
Technical path
We have production AI and need adversarial validation.
Scope the exposure, red team the system, then harden the control path.
Focused scoping
AI-RTA
Hardening plan
Scale path
We need to know whether AI adoption is mature enough to scale.
Start with maturity, go deeper on security where needed, then execute against the roadmap.
AIMA
AISPA
Execution support
If EU exposure is in scope, add the EU AI Act readiness module to AISPA or AIMA rather than treating it as a separate first move.
Why RAXE
Enough rigor to defend the work. Enough clarity to drive a decision.
01
AI-native
Built for agents, LLM applications, RAG, model serving, and AI supply chain exposure. Not generic consulting with AI language layered on top.
02
Evidence-led
Findings are tied to interviews, artefacts, telemetry, configurations, and test evidence. The buyer gets a position they can defend.
03
Response-oriented
The output is written so leadership, security, engineering, legal, and business owners know what happens next, by whom, and by when.
04
Product-aware, not product-led
RAXE controls can fit where relevant, but the logic stays control-first. Risk, evidence, and action come before product discussion.
Who leads the work
Mukund Hirani
Founder · RAXE AI Security
Mukund Hirani has worked across national security, incident response, threat intelligence, and enterprise security environments, including GCHQ, Mandiant, FireEye, and CrowdStrike. That experience shapes RAXE advisory work: evidence-led, operationally grounded, and focused on the decisions leaders need to defend.
GCHQ
Mandiant
FireEye
CrowdStrike
Framework alignment
Every engagement maps to the standards your audit, board, and regulators already recognise.
Findings, scorecards, and action registers are structured so they drop straight into existing governance, risk, and compliance workflows — not in parallel to them.
NIST
AI Risk Management Framework
OWASP
LLM Top 10 · ML Top 10
MITRE
ATLAS adversarial ML
ISO/IEC
42001 AI management
Next step
Scope your engagement in a 30-minute call.
You leave with three things: a clear first move, a success definition you can share with leadership, and a timeline you can plan against.
Book a 30-minute scoping call
or share scope in writing →
Scope depends on business units involved, evidence depth, production AI footprint, stakeholder count, and reporting needs.