Claude AI Transformation Services
PME Consulting helps enterprise transformation leaders move Claude from pilots to governed production workflows — across program delivery, software modernization, and AI-enabled operating models.
Who We Help
We work with CIOs, CTOs, CDOs, transformation executives, PMO leaders, and professional services firms who have moved past the question of whether to adopt AI and are now accountable for a harder one: making it work inside a real enterprise — with its security constraints, regulatory obligations, delivery commitments, and people.
A successful pilot is not the same as a system a business can run on. The distance between the two is integration, evaluation, governance, and the way people's work changes. That distance is where most enterprise AI initiatives stall — and it is exactly where PME operates.
This is not a new discipline for us. It is the same execution gap we have spent two decades closing on SAP, Salesforce, and platform transformations. Claude raises the stakes and compresses the timeline. The discipline required to land it is the one we already practice.
How We Engage
Each engagement is scoped to where your organization actually is: evaluating, deploying, or scaling. All three share one principle — production discipline from day one.
01
Two to four weeks. From AI ambition to a governed adoption roadmap.
For organizations deciding where Claude creates real value and what it takes to deploy it responsibly. We assess your use cases against business value, map security and compliance constraints, and design the operating model — so the first deployment is built for production, not just demonstration.
02
AI-assisted program governance for enterprise transformation delivery.
For transformation offices and PMOs that want delivery operations at the standard of the technology they are implementing. We embed Claude into the governance workflows we have run for two decades: status synthesis, RAID management, decision logs, gate readiness, and executive reporting — with humans holding authority over every gate.
03
AI-assisted engineering, delivered with enterprise discipline.
For engineering and platform leaders modernizing legacy estates or accelerating delivery with Claude Code. We combine developer enablement with the governance layer most AI coding rollouts skip: review gates, quality controls, and delivery metrics that let leadership trust what ships.
Model Choice
We start with Claude because that is where our practice runs today. PME Consulting is a member of Anthropic's Claude Partner Network. But enterprise AI in 2026 runs on a mix of proprietary and open models, and the governance we build does not change when the model does. Decision rights, gate criteria, audit trails and adoption measures are model-independent by design, so a workload can move between Claude and an open model inside your own boundary without the program losing control.
Why PME
Most AI services firms know models. PME knows why enterprise transformations fail — because we have spent more than two decades inside them: SAP and Salesforce programs, regulated industries, multi-vendor delivery, executive governance, recovery of programs that drifted off course.
That experience produces a specific conviction: Claude creates enterprise value only when it is embedded into governed workflows — decision rights, delivery cadence, auditability, and change adoption. Deployed without that structure, AI accelerates activity. Embedded with it, AI accelerates outcomes.
"AI agents execute. Humans govern through gates."
— The operating principle across our AI practice
We hold ourselves to the same standard we bring to clients. Our own product, TransformOps SF, is built with AI-assisted delivery governed through explicit gates — we run our own programs on the discipline we recommend. And we are building a team of Claude-certified practitioners through Anthropic Academy, spanning transformation leadership, solution architecture, engineering, security, finance and audit, and change enablement.
That team runs especially deep in regulated financial environments. With senior finance, audit, and capital-markets leadership alongside our transformation principals, we are well positioned to bring Claude into banking, capital-markets, and fintech organizations — where AI adoption has to satisfy the controls, auditability, and regulatory obligations these institutions answer to.
Who builds it
Governance and delivery on every engagement are led by PME's Principals. The systems themselves, the workflows, the agents, and the production infrastructure they run on, are built and kept running by the engineering side of the practice.
Nikita Alexeev takes an AI system from the first client conversation to the day it goes live, and then owns what happens next: the uptime, the cost, and the call at three in the morning.
He works from Innovation Park Stavanger with oil and gas, subsea, and maritime clients, covering AI automation and enablement, computer vision, outreach automation, dashboards and internal tools, and web products, from discovery and architecture through implementation, integration, deployment, monitoring, evaluation, and guardrails.
The work itself is production n8n workflows, agentic systems built on Claude and MCP tool servers, RAG and computer vision pipelines, the servers, tunnels, and watchdogs that keep them running, and the guardrails and on-device AI that keep them safe.
Every system he builds is one a client can open and use today.
Certifications: Anthropic · n8n · Microsoft.
He builds the way this practice sells: AI-assisted, with the architecture, the guardrails, and the operations owned by a human.
Governance & Responsible AI
Every engagement carries the same non-negotiables. Human authority over consequential decisions: AI drafts, analyzes, and accelerates; people approve, classify, and own outcomes. Auditability: AI-assisted work is traceable — what was generated, what was reviewed, what was accepted, and by whom. Security and data discipline: deployments respect your data boundaries, regulatory obligations, and security architecture from the first workshop, not as an afterthought.
We design for the question your auditors, regulators, and board will eventually ask: who authorized this, and how do you know it works? Organizations that can answer it scale AI with confidence. Organizations that cannot, stall — usually right after the pilot.
Let's Talk
We don't pitch. We diagnose. Tell us where your AI adoption actually stands — we'll tell you what we see and whether we can move it to production.
Discuss Your AI Program