We assess the AI already running in your environment, design what should be there, and deploy it on your stack — in a report your CISO, CTO, and auditor can all read.
The real problem
Shadow tools deployed without IT review. Licensed products — Copilot, Claude, Codex — sitting largely unused because no one trained the people who bought them. Integrations crossing data boundaries without anyone noticing. Sensitive data flowing into commercial models with no retention contract on record.
Regulatory exposure from AI tools your auditor will eventually ask about. Wasted spend on licenses generating no value. Missed automation that could recover thousands of hours — if adoption had been addressed. Security debt that compounds silently until it doesn’t.
The assessment
Our primary product is an assessment conducted inside your environment. You receive a written report covering every dimension, with a prioritized implementation roadmap attached.
Every AI tool in use across your organization — licensed, shadow, or embedded — catalogued by team, use case, and data exposure. Including what your people are doing with Claude, Copilot, Codex, ChatGPT, and any vendor-embedded AI in your existing stack.
Where AI touches sensitive data, who has access, what leaves your environment, and what doesn’t. Data residency, third-party model contracts, API exposure, and credential handling — reviewed against your current security controls.
Based on your enterprise architecture, we map where AI belongs and where it creates structural risk. Private versus cloud inference, integration patterns, retrieval boundaries, and the controls your security team already trusts.
Which tools in your current stack are worth keeping, what’s redundant, what capabilities you already have that teams aren’t using, and what’s genuinely missing. With specific integration guidance for everything we recommend.
Data boundary, audit trail, identity, model version, rollback, reviewer records — scored against the standard your regulator applies. Each gap documented with a clear closure path and the evidence format your auditor will accept.
Adoption assessment across your teams. What people are actually doing, what they’re avoiding, and where they’re improvising in ways that create risk. A training plan is included in every engagement.
Where the hours come back
Every phase produces something written
Every deliverable is written, dated, and signed before we move to the next phase.
Your AI footprint, mapped.
What you’re running, what’s at risk, what’s missing — across all six dimensions. Scored, evidenced, and paired with a prioritized implementation roadmap.
The stack you should have.
Tool decisions, integration patterns, data boundaries, private vs. cloud — written against your existing enterprise architecture.
One file your auditor opens.
Inputs, prompts, models, outputs, reviewers — linked, hashed, and retained as a single packet your auditor can open.
Your tools. Your use cases.
Instruction on the tools your teams already have, at the level your regulatory environment requires.
Training your teams on AI
Copilot, Claude, Codex, and ChatGPT are already running inside most regulated organizations — often without IT’s full knowledge, and almost always without structured instruction on what to share, what not to, or how to get useful output within compliance boundaries. We assess how your teams are using AI today and deliver training built around your tools, your use cases, and your regulatory context. Not generic AI awareness. Specific, practical, auditable.
What to share, what not to, and how your data policies apply to AI tools.
How models work, where they fail, and what that means for your work.
Practical instruction on M365 Copilot for documents, meetings, and email.
Prompting, code generation, and safe integration within your environment.
Completions, code review, and workflow integration for engineering teams.
Scripting, automation, and building lightweight AI tools on your stack.
What your board, CISO, and auditor need to understand about AI risk.
Structured prompting for reliable, auditable, repeatable outputs.
AI agents, automated pipelines, and where human oversight is required.
Standalone training as a service. Individual courses and cohort/corporate sessions available.
Pick where the work is stuck
We audit your current AI usage, security posture, architecture fit, tool landscape, governance gaps, and user readiness. You leave with a scored report and a sequenced implementation plan.
Reference architecture built on your existing stack. Which tools to use, how to integrate them securely, what to allow, what to restrict, and whether private AI infrastructure belongs in your environment.
We stand the workflows up in your environment, on your stack, with your controls. We train your teams on the tools — your tools, your use cases, your boundaries. Then we hand it over.
How we work
We work where controls are not optional
Answers in writing
Yes. User readiness is one of the six dimensions in every assessment. We look at what tools your teams have, what they’re actually doing with them, where they’re improvising unsafely, and what training would close the gap. The training programme is included in the deployment engagement — covering your tools, your use cases, and your compliance boundaries. Not generic AI training.
That’s one of the core architecture decisions the assessment produces. The answer depends on your data classification, regulatory context, latency requirements, and the controls your security team already has in place. We document the decision, name the reasoning, and sign it — so it’s a written, evidenced conclusion, not an informal judgment call made during a vendor sales process.
We don’t sell tools and we have no preferred vendors. We assess what’s right for your specific stack, regulatory environment, and team — and we say so in writing before any deployment begins. If a tool you already have is the right answer, we’ll tell you. If it isn’t, we’ll tell you that too. Our fee is fixed and does not change based on which tools you adopt.
A governed workflow is one where data boundary, identity, prompt, model, output, reviewer, and retention are all written down before code is shipped, and where every run produces a linked, hash-stamped record that an auditor can open later. If any of those is missing, the work is not yet governed.
We score across six dimensions — data boundary, audit trail, identity, retrieval, rollback, and vendor posture — each on a 0–100 scale with documented evidence per score. The overall score is a weighted average; we tell you the weights, and we tell you which dimensions a regulator will check first.
The evidence packet — input, prompt, model version, output, reviewer, timestamp, and hash — is what auditors ask for, in the form they ask for it. We have walked the artifact through audits in finance, healthcare, energy, and public sector. You keep the packets, not us.
Every deployed workflow is pinned to a model version and ships with a rollback contract — written, signed, tested before production. Rollback is a normal operational lever, not an incident response.
Yours. Your cloud accounts, your identity provider, your secret manager, your observability. We are tool-agnostic and stack-agnostic by design — we deploy where you already operate, against the controls your security team already trusts.
Handover is the deliverable. Runbooks, on-call shape, retention contracts, dashboards, and the documented architecture are part of the engagement. We do not retain the workflow; you operate it from day one of production.
From a clean intake: 2–3 weeks for the readiness brief, 3–5 weeks for architecture design, 6–10 weeks for deployment. Most teams want a smaller first slice in production before they widen scope — we plan for that.
Only where you have written, signed permission for it to. Most engagements run with in-region inference and a closed data boundary. Where a third-party model is used, the contract is named, the residency is named, and the retention is named in the architecture document.
Your identity provider, your roles, your groups. No shadow identities, no service accounts standing in for real reviewers. Every action against the workflow resolves to a named person via your IdP.
A small, named team. The architect who wrote your design is the same person who deploys it. There is no offshore handoff and no rotating delivery team. You will have phone numbers.
Fixed-fee engagements priced by scope, not by hours. We send the price in writing before we begin, and we do not bill against scope changes we did not warn you about.
Start with the assessment
Two to six weeks. A complete picture of what AI you’re running, what’s at risk, and what to build next — written, scored, and signed.