Each layer answers a concrete operational question about how AI fits into procurement work. Together they form a system — not a slide deck, not a folder of prompts. PAIR Assessment is always the entry point; the rest is implemented based on what the diagnosis surfaces.
A 2-3 week structured diagnostic. We map procurement processes with your team, score AI use cases by value and feasibility, check data and team readiness, and deliver a 90-day implementation roadmap. PAIR is what separates teams that build a real AI Operating Model from teams that accumulate ChatGPT screenshots.
Repeatable AI-assisted sequences for real procurement work. Not one-off prompts — workflows with defined inputs, processing steps, quality checks, human-in-the-loop decisions, and audit trails. Each workflow targets a specific moment in the procurement cycle.
Tested prompts, lightweight agents and instructions packaged for repeated team use. Each has clear inputs, expected outputs, QA checks, and role variants. Built once, used by the whole team — buyers stop reinventing the same prompt from scratch.
What AI can actually see. Most AI procurement experiments fail not because of the model but because of the data — inconsistent supplier names, ERP exports with hidden tabs and ghost rows, sensitive contractual data that cannot leave the tenant. We define the data layer before workflows ship.
What AI may decide alone, what humans must approve, what cannot be automated. How decisions get documented so they remain auditable six months later. For European teams this is GDPR first, AI Act second — without governance the operating model becomes a compliance risk rather than a competitive advantage.
A dedicated training program built around your team, your processes and your chosen tools — not a generic AI course. Without this layer no Operating Model survives the third week. We deliver structured training plus champions inside the team, weekly clinics, adoption metrics and a follow-up rhythm that keeps AI in actual use.
Vendor-agnostic selection and integration. We don't have partnership deals or vendor commissions — the tool decision follows the workflow and data requirements, not the other way around. Most often: Microsoft 365 stack, Google Workspace, OpenAI or Anthropic with n8n orchestration, or a hybrid combining what you already operate.
Mid-cap European manufacturer. Procurement organisation of 50 people across three sites. Annual addressable spend around EUR 350 million. Existing ERP exports rather than API access. ChatGPT Team licence used by maybe a quarter of the team — each in a different way.
PAIR Assessment surfaces twelve scoreable use cases. We choose three for the first sprint — offer comparison for indirect categories, supplier scorecard preparation for top 20 strategic suppliers, and first contract review for new NDA / MSA work. Each workflow gets specced, built, governance-reviewed, and rolled out with dedicated team training. Adoption tracked weekly.
After ninety days the team owns three repeatable workflows running on real data, a documented governance baseline, a prompt and agent pack maintained internally, and a queue of nine more use cases ready for the next sprint — without needing a consultant for each step.
Illustrative composite based on the engagement structure. Specific client details are anonymised.
For procurement leaders ready to move from AI experiments to a working operating model.
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