Skip to content

What we do

Services

Advisory engagements spanning AI readiness, hybrid architecture and Zero Trust identity.

Service 01

Hybrid AI Strategy & Reference Architecture

Most mid-market AI adoption stalls on a placement question nobody has answered deliberately: which workloads can run in a vendor’s cloud, which need to stay on hardware you control, and why. This engagement works through that decision workload by workload, then documents the architecture that joins the two environments — data paths, model hosting, network boundaries — under a single identity layer, so the answer holds as more workloads get added rather than being re-argued each time.

What you get

  • A workload-by-workload placement decision — cloud, on-prem, or both — with the reasoning behind each
  • A reference architecture diagram covering data paths, model hosting and network boundaries
  • An identity-layer integration plan spanning both environments
  • A sequenced adoption roadmap with milestones and dependencies
  • An executive briefing deck built for leadership sign-off

Outcomes

  • Every AI workload assigned an explicit hosting decision and an owner
  • One identity model governing access across cloud and on-prem systems
  • A roadmap leadership can approve and budget against, sequenced rather than all-at-once

Service 02

AI Governance & Readiness Assessment

AI tools tend to show up in an organization ahead of any policy governing them — a team trials something, it works, and it quietly becomes part of how the work gets done. This assessment produces a structured read on where that has already happened: what tools are in use, what data they can reach, and which controls — acceptable use, data classification, vendor and model review — are missing before a new tool is allowed anywhere near production data.

What you get

  • An inventory of AI tools and models currently in use, sanctioned or not
  • A data classification review scoped to what those tools can reach
  • A ranked findings report with an owner assigned to each gap
  • A vendor and model review checklist for future approvals
  • A draft acceptable-use policy ready for legal review

Outcomes

  • A complete inventory of AI tools in use, shadow IT included
  • Every identified gap assigned an owner and a remediation deadline
  • A repeatable approval path in place for the next new tool request

Service 03

Identity-Centric Zero Trust Design

Access control built on network location or static roles breaks the moment an AI system starts making requests on a user’s behalf — there is no IP range or VLAN to anchor a policy to. This engagement rebuilds access around identity instead: directory and joiner-mover-leaver hygiene, conditional and privileged access, and segmentation derived from who and what is asking, not where the request originated from.

What you get

  • A directory and joiner-mover-leaver process audit
  • A conditional access and privileged access policy set
  • A segmentation model derived from identity rather than network topology
  • A phased rollout plan sequenced to avoid disrupting daily operations
  • A monitoring and alerting design for policy violations

Outcomes

  • Access decisions traceable to a single identity policy, not per-system exceptions
  • Standing privileged access reduced and replaced with just-in-time grants
  • Policy coverage extended to AI agents acting on user credentials

Service 04

AI Tooling Adoption & Enablement

A successful pilot and a successful rollout are different problems. This engagement takes a tool from a handful of willing users to daily use across a team: selection criteria, a wave-based rollout sequenced by risk, controls wired into the identity layer before go-live rather than bolted on after, and enablement material for the people who will actually use it — on the assumption that no one is being hired to run it full time.

What you get

  • Tool selection criteria and a shortlist evaluation
  • A wave-based rollout plan sequenced by team and risk
  • Controls wired into the identity layer — access, logging, DLP — before go-live
  • Enablement material and training sessions for end users
  • An adoption metrics definition for tracking usage after launch

Outcomes

  • Rollout completed wave by wave with no unplanned access incidents
  • Usage and adoption tracked against a defined metric from week one
  • Day-to-day support handed off to existing staff, no new hires required

How we work

Three ways to engage

Every service above can run under any of these three structures, depending on whether the question in front of you is bounded, ongoing, or an implementation.

ModelBest forTypical durationPricingEngagement style
Fixed-fee assessmentA defined question — readiness, architecture, gap analysis3–6 weeksFixed fee, scoped up frontOne deliverable, one findings review with leadership, then done
Advisory retainerOngoing decisions that don’t fit a single projectMonthly, open-endedFixed monthly rateStanding access for reviews, second opinions and course corrections
Project engagementImplementation work — rollout, policy build-out, migration8–12+ weeksFixed fee per phase, milestone-basedStaged delivery with sign-off gates between phases