AI9 min read
What is enterprise AI architecture?
The difference between a successful pilot and a production AI capability is rarely the model. It is the architecture around it. Here is what that architecture contains and which decisions matter.
Enterprise Architecture
Decisions that hold up for years, made with the whole landscape in view.
Enterprise and solution architecture for companies where AI, data, cloud and integration have to fit together: target architectures, technology roadmaps, assessments and governance grounded in real delivery experience.
The problem
Why technology estates become hard to change
Each project made a reasonable local decision. Nobody owned the whole picture, and the sum of those decisions is now the constraint.
01
Architecture by accident
Platforms chosen per project, overlapping tools, and integration patterns that differ from team to team.
02
Roadmaps that are wish lists
Initiatives without dependencies, sequencing or the capabilities each one unlocks, so priorities change every quarter.
03
Cost without visibility
Licenses, cloud, support and people spread across budgets, with no total cost of ownership per capability.
04
AI arriving on a fragile base
New AI initiatives expose gaps in data, integration and security that were never resolved.
Business impact
What architecture done well changes
A clear target and a sequenced roadmap turn technology from a series of projects into a platform that compounds.
Decisions with context
Every platform choice is evaluated against the target architecture, not in isolation.
A roadmap people can execute
Initiatives are sequenced by dependency and value, with the capabilities each phase unlocks made explicit.
Cost that can be managed
TCO per capability makes consolidation, retirement and renegotiation visible.
Foundation for AI and data
Integration, data and security capabilities are planned as prerequisites, not surprises.
What we deliver
What we deliver
Architecture as a practical discipline: documents that lead to decisions, and decisions that lead to delivery.
Architecture assessment
Current-state review of applications, data, integration, cloud and security, with findings ranked by risk and opportunity.
- Assessment
- Current State
Target architecture and roadmap
Capability map, target architecture, transition states and a sequenced technology roadmap with dependencies and estimates.
- Target Architecture
- Technology Roadmap
Solution architecture
Hands-on architecture for specific initiatives: AI platforms, data platforms, integration programs and cloud migrations, from design to delivery oversight.
- Solution Architecture
- Design
Technology strategy and selection
Platform evaluations, proof of concept design, vendor comparison and build versus buy decisions grounded in your constraints.
- Technology Strategy
- Selection
TCO and business case
Total cost of ownership models for platforms and initiatives, including licenses, cloud, people and risk, to support investment decisions.
- TCO
- Business Case
Architecture governance
Principles, standards, review processes and decision records that keep delivery teams aligned without slowing them down.
- Governance
- Standards
How we work
How we work
Weeks, not quarters. Architecture that stays close to the people who deliver.
- 01
Understand
We interview stakeholders, review systems and documentation, and map business capabilities to the technology that supports them.
- 02
Assess
We evaluate fitness, risk, cost and modernization potential per capability and platform.
- 03
Design
We define the target architecture, principles and transition states, and validate them with the teams who will build.
- 04
Sequence and support
We produce the roadmap, business case and governance, and stay involved as solution architects during execution.
Reference architecture
How we frame the enterprise landscape
Business capabilities on top, technology platforms below, and the architecture decisions that connect them.
01Business
- Capabilities and processes
- Channels and customers
- Regulatory and risk context
02Applications
- Systems of record
- Systems of engagement
- Products and SaaS
03Data and AI
- Data platform and governance
- Analytics and semantic layer
- AI services and agents
04Integration
- APIs and events
- Middleware and messaging
- B2B and partners
05Infrastructure
- Cloud landing zones
- Hybrid connectivity
- Security and identity
06Governance
- Principles and standards
- Decision records
- Cost and lifecycle
We keep frameworks such as TOGAF in the background. The deliverable is a set of decisions your teams can act on.
Technologies
Where our architecture experience comes from
Architecture advice is only as good as the delivery behind it. Ours comes from years of building on these platforms.
Integration
- IBM App Connect and API Connect
- Oracle SOA Suite and OIC
- MuleSoft
- Boomi
- ServiceNow IntegrationHub
- Apache Kafka
Cloud
- Microsoft Azure
- AWS
- Google Cloud
- Kubernetes and serverless
Data
- Microsoft Fabric
- Databricks
- Power BI
- Lakehouse architectures
AI
- Azure OpenAI and AWS Bedrock
- RAG and agents
- LangChain and LangGraph
- AI governance
Enterprise systems
- SAP
- Salesforce
- ServiceNow
- Oracle applications
- Infor CloudSuite
- Custom and legacy platforms
Benefits
Benefits
- Fewer expensive reversalsPlatform decisions evaluated against the whole landscape before money is committed.
- Clear prioritiesA roadmap sequenced by dependency and value that survives quarterly planning.
- Lower total costConsolidation and retirement opportunities made visible through TCO per capability.
- Readiness for AIData, integration and security prerequisites planned before the first AI project.
- AlignmentBusiness, IT and delivery teams working from the same picture.
- ContinuityArchitects who stay through delivery instead of handing over a document.
Use cases
Typical scenarios
When companies bring us in for architecture work.
Pre-investment assessment
Before a large AI, cloud or integration program, an independent view of readiness, options and cost.
Technology roadmap
A multi-year plan connecting business goals to platform decisions and sequenced initiatives.
Platform consolidation
Rationalizing overlapping integration, data or cloud tools accumulated over years or acquisitions.
Solution architecture for a critical initiative
A senior architect leading the design of an AI platform, data platform or migration.
Architecture function setup
Establishing principles, review processes and decision records for a growing IT organization.
Due diligence
Technical assessment of a technology estate for mergers, acquisitions or outsourcing decisions.
FAQ
Frequently asked questions
What is the difference between enterprise architecture and solution architecture?
Enterprise architecture looks at the whole landscape: capabilities, platforms, roadmap and governance. Solution architecture designs a specific initiative within that landscape. We do both, and we believe they only work when the same people move between them.
Do you follow TOGAF or another framework?
We use frameworks as a vocabulary, not as a process to be followed literally. The deliverables are sized to your organization: enough structure to make decisions repeatable, not so much that architecture becomes a bottleneck.
How long does an architecture assessment take?
It depends on the scope and the size of the landscape. We scope assessments to deliver findings and recommendations in weeks, with a clear definition of what is covered and which decisions the assessment is meant to support.
Can you stay involved during implementation?
Yes, and we recommend it. Architecture decisions are tested during delivery. We act as solution architects alongside your teams or delivery partners so the target architecture is actually built.
How do you calculate total cost of ownership?
We model licenses, cloud consumption, infrastructure, support, people and transition costs per capability over a multi-year horizon, and compare scenarios such as keeping, modernizing or replacing a platform.
Related solutions
Related solutions
Digital Transformation
Turn the roadmap into a modernization program.
AI & Generative AI
Place AI initiatives on a solid architectural base.
Enterprise Integration
The layer most architecture decisions depend on.
Insights
Related insights
Cloud9 min read
Cloud modernization strategy: how to modernize legacy systems without stopping the business
Moving to the cloud is the easy part. Making legacy systems cheaper to run and faster to change is the goal. A strategy built from assessments and migrations in real enterprise environments.
Integration9 min read
SOA vs microservices: enterprise integration architecture that lasts
The debate is usually framed as old versus new. In practice, enterprises that integrate well take the principles of SOA, the autonomy of microservices and the governance of API management, and evolve toward them one interface at a time.
Get an independent view of your architecture.
An assessment gives you findings, options and a sequenced roadmap you can take to the board.