Workflow portfolio
Prioritised use cases with users, inputs, decisions, expected value, constraints and success measures.
AI TRANSFORMATION · SYSTEMS & OPERATIONS
For organisations moving from
isolated pilots to production.
AI transformation,
engineered.
( 01 — TRANSFORMATION OUTPUT )
Decide what changes.
Then make it work.
We turn a broad AI ambition into a bounded portfolio of workflows, systems, owners and delivery stages. Each stage ends in something that can be tested.
Target architecture
Data, knowledge, models, tools, integrations, permissions, controls and deployment boundaries.
Operating model
Named owners, approval paths, quality review, incident handling, vendor management and change control.
Delivery roadmap
Sequenced production increments, dependencies, evidence gates, adoption work and investment decisions.
( 02 — TRANSFORMATION SYSTEM )
Workflow to
operation.
Transformation is complete only when the workflow, technical system and operating responsibility work together.
Business workflow
User · decision · inputs · exception · outcome
Defined valueData and architecture
Context · models · tools · integration · deployment
Working productGovernance and evidence
Identity · oversight · evaluations · records · incidents
Reviewable riskOwnership and adoption
Owners · training · support · measurement · change
Sustained useCompliance is part of the architecture. Where regulation applies, we work with your legal and risk teams to convert their interpretation into technical controls and evidence.
AI regulation readiness ↗( 03 — DELIVERY PATH )
Start bounded.
Expand on evidence.
The programme is scoped around real workflows and existing systems. A transformation mapping engagement typically costs €12,000–€25,000; production builds are quoted against the agreed architecture and acceptance measures.
Map.
Select workflows, establish baselines, map systems and constraints, and define the target operating boundary.
Build.
Ship a production increment with real data, integrations, evaluations, permissions and reviewable controls.
Operate.
Measure adoption and quality, transfer ownership, harden runbooks and expand only where the evidence supports it.
( 04 — MEASUREMENT CONTRACT )
Evidence before
expansion.
We do not publish invented client outcomes. Every engagement instead begins with a baseline and ends with a reviewable measurement record.
Task acceptance
Representative evaluation set, failure categories and an agreed pass threshold.
Cycle time
Baseline human workflow time versus the assisted or automated production path.
Intervention rate
Approvals, exceptions, escalations and rejected actions by risk class.
Active use
Eligible users, successful sessions, repeat use and abandonment—with no advertising identifiers.
Unit cost
Model, infrastructure and human-review cost per accepted outcome.
Operational health
Latency, incidents, drift, rollback readiness and provider failover evidence.
( 05 — COMMON QUESTIONS )
Before the
programme.
What does AI transformation mean here?
Changing specific workflows, systems and operating responsibilities so AI produces measurable work in production. It is not a generic strategy deck or a collection of disconnected pilots.
Do you only advise or also build?
Both. N137.AI can map the portfolio and target architecture, build production increments, integrate controls and support ongoing operation.
Do we have to use a specific model or cloud?
No. We design business logic, controls and evaluation outside any single model provider so the system can use the deployment that fits your constraints.
How is AI compliance included?
Identity, permissions, human oversight, evaluations, records and incident processes are designed into the target system. Your counsel remains responsible for legal interpretation.
START WITH ONE WORKFLOW
Discuss the
transformation.
Tell us which workflow, system or business unit needs to change and what a useful production outcome would look like.
hello@n137.ai ↗