What reasons
OpenAI, Anthropic, Google Gemini, Microsoft and open-source models. The task chooses the model, never loyalty, and the design lets you change your mind.
Stage 3 · Design · the architecture
AI Architecture
Most AI agencies stop at “we’ll build you a chatbot”. We design how your people, data, AI models, agents, applications, automation and security work together, so what gets built runs your business instead of demonstrating it.
What architecture means here
An AI architecture is a set of decisions written down before anything is built
Which model answers which kind of question. What the AI is allowed to know. What it is allowed to do without asking. How it reaches your systems. What is logged. Who is accountable.
Write those decisions down first and the build is fast and boring. Skip them and every pilot becomes a negotiation, every demo impresses and nothing ships.
The intelligence layer
Six things that have to work together
One request through the layer
What a designed AI system actually does with a customer email
- 1A customer email arrivesIntegration hands it to the agent with the customer record attached.
- 2The agent checks KnowledgeContract, history, policy. It cites what it used.
- 3A model drafts a replyLimited to what Knowledge returned. No inventing.
- 4The draft lands in Microsoft 365 as a taskNot as sent mail.
- 5A person approves, edits or rejectsConsequence needs a human. This is the design decision competitors skip.
- 6CRM updated, reply sent, follow-up scheduledBy automation, with nothing re-keyed.
- 7Every step loggedCost, quality and drift monitored under AI Managed.
Design principles
The five rules every Be AI architecture follows
- Knowledge before models. A weaker model with the right documents beats a stronger one guessing.
- Anything with a consequence waits for a person. Approval is a design feature, not a limitation.
- Integrate, don’t replace. The AI reaches into the systems you have; it does not become another one.
- Every action leaves a record you could show a customer, an auditor or a court.
- No vendor is load-bearing. The design must survive changing models, platforms and suppliers, including us.
Deliverables
What you own at the end
Questions
What people ask about AI Architecture
Can you design on the Microsoft stack we already own?
Usually that is the right answer, and the design says exactly which of your existing licences already cover what. We deploy on Azure and Microsoft 365 with Be Cloud where that is the fit, and elsewhere when it is not.
Do we have to build agents, or can we just use Copilot?
Copilot is often step one. The architecture is what makes step two possible without starting again, because it decides the knowledge, permissions and approval design that Copilot inherits.
Who owns the architecture?
You do. It is written so any competent team can build from it, and it names platforms, not Be AI dependencies.
How is this different from an IT architecture?
It includes the model, the knowledge and the approval design, which is where AI projects actually fail. An IT architecture tells you where the servers are. An AI architecture tells you what the system is allowed to know and do.
Related
Keep exploring
The difference between a demo and a system you run your business on is the design.
Thirty minutes with an AI architect, no slides, and a written note afterwards on what we would design first and why.