Service · AI
AI Consulting
AI capability your team owns, from readiness assessment through implementation to a measured review after go-live.
- readiness
- framework
- assessment
- governance
- skills
Overview
We build AI capability your team owns and sustains, not a dependency on us. Engagements cover the full adoption lifecycle: deciding where to start, designing and implementing an AI SDLC framework around your delivery process, and maturing a practice already running. A ten-skill curriculum coaches your people on the habits that separate teams doing real work with AI from teams that bounce off it. Once the framework has run on live delivery, we measure adoption, surface the gaps, and hand your leadership a prioritized roadmap for the next stage.
What the engagement covers
- Readiness assessment that scores toolchain, team capability, process maturity, and organizational appetite against a clear framework
- AI SDLC framework design and implementation: agent configuration, codebase onboarding, skills library setup, and team enablement across every delivery phase
- AI skills curriculum: the ten habits that decide whether AI work lands or wastes time, scored per person on a five-point scale and coached against live work, not in a classroom
- Free self-assessment: your team scores itself in about ten minutes and sees the three skills to address first, no sales call required
- Existing AI framework assessment that measures adoption, quality-gate effectiveness, agent accuracy, and team satisfaction
- Maturity roadmap: every assessment ends in a prioritized improvement plan with named ownership
- AI governance: quality gates, human approval workflows, audit trails, and responsible AI policy, so every AI action is logged, attributable, and defensible
- Governance that reaches the org chart: we hand the operating model to Workforce Transformation, where it becomes the way roles, reviews, and approvals actually run
- Use case identification ranked by business value and effort, then time-boxed prototyping
- Technical-debt work: AI-driven code analysis, targeted refactoring programs, and automated documentation generation
Select what you need
Five ways in. Choose one.
These are options, not stages. Take the one that matches where you are, and add the others when you are ready for them.
Option
AI Readiness Assessment
We audit your development stack, team capability, toolchain, and process maturity. We assess organizational readiness across culture, governance appetite, and risk tolerance, then name the integration points worth taking first. Output: a scored readiness report and a recommended adoption path.
Option
AI SDLC Framework Design & Implementation
We design the framework around your delivery process, then configure its agents to your conventions, tech stack, and team workflows. We onboard your codebases, wire up integrations (Jira, Confluence, CI/CD, monitoring), and run a focused pilot on live workstreams. Your developers judge the result on their own work: bug fixes, code reviews, test generation, and documentation.
Option
Existing AI Framework Assessment
Already running an AI framework, ours or anyone else's? We run a structured review of it. We measure adoption depth, quality-gate pass rates, agent accuracy, rework, and developer satisfaction. You get a gap analysis and a prioritized roadmap for what comes next: new agents, broader codebase coverage, or deeper capability.
Option
AI Governance Design
AI moves fastest exactly where nobody is watching. We design the governance that keeps it accountable: quality gates before merge, human approval at the points that carry risk, and an audit trail that records what the AI did and why. Your compliance team reads evidence rather than assurances, and your board gets an answer to who approved what. Where governance has to change how people work day to day, it carries into Workforce Transformation.
Option
AI Skills Coaching & Sustainment
The curriculum coaches your people on the habits that decide whether AI work lands or wastes time. The coach narrates the skill in play while real work happens. Intake and exit scorecards make the change visible, and a follow-up assessment later in the year checks that the habits stuck. As the practice matures, we extend the framework across teams and codebases, build custom agents for domain-specific workflows, and run regular health checks.
Every engagement
Four phases, whichever service you take
The shape does not change between services. What changes is the work inside it.
01
Discovery
Every engagement opens here. We establish how your teams deliver today, not how the process document says they do, and name what is worth taking first.
02
Collaborative delivery
We work inside your delivery rather than beside it, on live workstreams your teams already own. Your people judge the result on their own work.
03
Skills and enablement
We coach your people on the habits that decide whether the change holds after we leave. Capability stays with your teams rather than with us.
04
Evaluation and summary
We measure what the engagement changed against what we set out to do, and hand your leadership a written summary at the close.
Ready to explore AI Consulting?
Book a call and walk us through how your teams build today. We name the risks, map the work, and set out what changes.