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Interactive demo · Build & Foundations

AI Architecture Agent Teams

One blueprint your whole org builds against. Watch how we take your systems, data flows, and AI footprint from where it is today to live in production. Analyze, assess, build, deploy.

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ai-architecture-teams.dnai
architecture.ai · system designReference architecture · model routingClient appsAPI gatewayAuth · ACLModel routerRetrievalGuardrailsClaudeGeminiPrivate LLMTools / DB

Illustrative product view · interact with the live build below

01
AnalyzeInteractive

We map your systems, data flows, and AI footprint.

Before we build anything, we scan your current surface and surface exactly what is working, what is broken, and where the upside is hiding.

systems · data · model calls
Analyzing

Mapping systems, data flows, and where AI is wired in…

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  • 1AI pilots in flightsiloed, no shared platformGap
  • 2Model callsscattered across servicesIssue
  • 3Reference architecturenone; tribal knowledgeIssue
  • 4Data-flow + lineage docspartialGap
  • 5Cost / latency visibilityper-call, unmonitoredGap
  • 6Security + ACL boundariesinconsistentIssue
What we found: Promising pilots, but no shared architecture to scale them safely or cheaply.

Illustrative scan of a representative current-state surface. Your live engagement maps your real data.

02
AssessInteractive

We score the opportunity.

Every move is plotted by impact against effort on your own data, so the first build is the obvious, defensible one, not a guess.

opportunity.dnai
What makes AI scale across the org, by impact vs. effort.scored on your data
Impact
Low effortHigh effort
Reference architecture + ADRsimpact 90effort 40

One documented blueprint your teams build against.

The plan: Set the reference architecture and a governed model router first; every later build snaps to it.1Reference architecture, org-wide
03
BuildInteractive

We build it on your stack.

One blueprint your whole org builds against. Assembled stage by stage over your real tools, tested and shipped to production with a clear owner at every step.

build.dnai
Building on your stack
integration.log
→Map systems…
04
DeployInteractive

It runs live.

Here is what your team sees once it is in production: the dashboard, the numbers, and the work moving on its own.

0%
Pilots on one platform
0%
Model routing, governed
0%
Architecture decisions documented
reference-architecture.dnai
Reference architecture5 layers · every decision recorded
Model routerDecided
Decision
Vendor-neutral router; route by task, cost, and latency budget
Trade-off
Small routing overhead vs. avoiding lock-in and runaway spend
Fallback
Secondary provider on timeout or error, no single point of failure
Status
ADR-04 accepted · cost ceilings + guardrails attached

Illustrative demo data. The live engagement maps your real systems, designs the architecture against your constraints, and hands your engineers the decision records and infrastructure-as-code to own it.

Live · What your team sees
›Mapped: 23 services, 6 data stores, 5 AI pilots
›Reference architecture - model router + RAG + guardrails
›11 ADRs - every trade-off documented
›Roadmap: 4 phases, owners assigned, IaC scaffolded

Want AI Architecture Agent Teams running on your network?

Book a 30-minute call. We will analyze your business, scope the build, and come back with a fixed plan and a numbers-anchored target.