Is this about GenAI only?
No. The service covers the full AI spectrum — from classical ML to large language models — wherever governance, deployment and data control are priorities.
AI governance, data foundations and deployable operating models for responsible, production-ready AI in regulated and complex environments.
PiR2-IT helps organisations turn AI ambition into deployable capability — combining data foundations, governance controls and operating models that work in production.
The problem. Most AI initiatives succeed in pilot and fail at scale. The gap is almost always governance, data quality and operating model — not model performance.
What this fixes. PiR2-IT designs the conditions for production AI — data readiness, governance controls embedded in the delivery lifecycle, and operating models with real ownership and decision rights.
What you get. A clearer AI operating model, stronger production readiness, governance evidence that satisfies regulatory scrutiny, and architecture decisions that support scalable, auditable AI.
Define roles, governance structures, decision rights and lifecycle responsibilities for enterprise or programme-level AI deployment — including human-in-the-loop controls.
Clarify data sources, ownership, quality, lineage and access patterns — the architectural conditions needed for reliable, auditable AI output at scale.
Model deployment pipelines, operational controls, drift monitoring, release governance and integration with existing platform and security constraints.
Explainability frameworks, review gates, bias controls and governance evidence embedded in the AI lifecycle — designed for regulated and high-trust environments.
Enterprise AI readiness reviews, AI operating model design, data foundation assessments, responsible AI controls, MLOps shaping and architecture support for AI-enabled modernisation programmes.
Banks, insurers and financial infrastructure providers deploying AI under DORA, SR 11-7 and emerging AI Act obligations.
National agencies, international organisations and public bodies where AI accountability and explainability are constitutional, not optional.
Mission-critical AI where data provenance, model integrity and human oversight controls are non-negotiable operational requirements.
No. The service covers the full AI spectrum — from classical ML to large language models — wherever governance, deployment and data control are priorities.
Governance becomes practical when it is designed alongside architecture and data decisions, not layered on top as documentation after the fact.
When pilots exist but scaling, auditing or governing them is unclear — or when regulatory pressure, programme complexity or data quality is blocking deployment.
Yes, deliberately. AI systems have distinct security surfaces. This service connects to cybersecurity architecture where AI and security requirements intersect.
Share the environment, constraints and objectives — and we can explore what the right engagement looks like.