From values, mission, and capabilities to executable Enterprise AI Architecture.
Design composable, agentic- and GenAI-ready architectures aligned to your values, missions, goals, and capabilities — interoperable, secure, and built for change.
Translate strategy into execution: prioritize use cases by value/feasibility, define measures, and stage adoption with clear milestones.
Assemble the right components step-by-step — data, integration, retrieval, agents, evaluation, observability, and controls. Models are a part, not the center.
Explore the logical, data, and runtime views we deliver as part of engagements. Jump to details below.
Deploy on public cloud, private cloud, or on‑prem data centers to meet security, geopolitical, economic, and privacy requirements without compromising agility.
Build-in safety, privacy, and compliance while optimizing for minimal environmental load and maximum business value and performance — maximize expected utility.
Foundational pipelines, quality, and governance that power AI and EA — essential and acknowledged, though not our primary focus area.
We follow a structured methodology to ensure successful AI architecture implementation
We begin by understanding your business challenges, existing infrastructure, and AI readiness to identify the best opportunities for transformation.
Based on our assessment, we create a tailored AI strategy with clear objectives, success metrics, and implementation roadmap.
We design a scalable and secure AI architecture that integrates with your existing systems while enabling future innovation.
Our team implements the architecture, develops AI models, and integrates them with your business processes and systems.
We establish monitoring systems and continuously optimize your AI architecture for performance, security, and business value.
We deliver a capability‑aligned, governed blueprint as part of EA Design, AI Delivery, Infra & Cloud, and Security & Sustainability.
Logical — channels, services, agent layer, models; anchored in capabilities and value streams.
Data — domain products, contracts, lineage, privacy; stewarded and governed by design.
Runtime — events, workflows, inference, guardrails; observability and change loops.
Prefer a deep dive? See the full reference views and notes on the Reference Architecture page.