Runs where
you choose.
Your cloud, VPC, private environment or on-premises infrastructure.
Scale cognition.
Master complexity.
Scale
cognition.
PLANREASONACT
( 01 — SOVEREIGNTY STANDARD )
Control is a
system property.
We design AI so the operating company—not a model vendor—controls deployment, data, policies and change.
Runs where
Access stays
explicit.
Identity, permissions, lineage and retention remain under your control.
Providers stay
replaceable.
Business logic sits outside any single model API or deployment mode.
Every action
is observable.
Logs, evaluations, approvals and human override are part of the system.
( 02 — PRODUCTION SYSTEMS )
What we
build.
N137.AI is an independent AI product and engineering company. We lead AI transformation, implement compliance controls and build the systems required to run AI inside a real business.
Each system is built around your infrastructure, identity, data permissions and operating constraints.
01Sovereign AI Control↗
Control every
model request.
Identity, policies, audit trails, guardrails, evaluations and provider routing in one layer.
02Private Knowledge↗
Make company
knowledge usable.
Permission-aware ingestion, retrieval, citations, data lineage and measurable answer quality.
03Operational Agents↗
Connect AI to
real work.
Agents use typed tools, explicit permissions, approval steps and observable actions.
( 03 — REFERENCE ARCHITECTURE )
The sovereign
stack.
Each layer can be owned, replaced and audited independently. Move across the stack to send a signal through the underlying topology.
Data sources
Files · APIs · databases · business systems
Knowledge layer
Ingest · validate · permissions · retrieval · citations
Agent runtime
Task state · tools · approvals · typed actions
Control plane
Identity · policy · guardrails · audit · evaluations
Model layer
Cloud models · private models · fallback routes
YOUR INFRASTRUCTURENO REQUIRED MODEL VENDOR
✳
N137 / PRODUCTION STANDARD
Production
requirements,
designed in.
Identity & accessPer-request logsEvaluation gates
Human approvalMonitoring & costProvider exit path
( 05 — AI GOVERNANCE )
AI regulation,
engineered.
We translate regulatory obligations into system controls and evidence: who may use a model, what it may do, how decisions are reviewed and what an auditor can inspect.
REGULATIONCONTROLEVIDENCE
Regulatory
readiness.
- AI system inventory
- Provider and deployer roles
- Risk and transparency classification
- Control gap map
Control
layer.
- Identity and permissions
- Human oversight
- Evaluation gates
- Model and vendor controls
Audit
evidence.
- Request and decision logs
- Model and version records
- Incident workflow
- Evidence export
( 06 — HOW WE WORK )
Senior-led delivery, shared repositories,
documented handover and continuity.
01Review
Review
the system.
We map the workflow, data, identity, dependencies, risks and measurable outcome.
02Design
Design
the architecture.
We define deployment, integrations, permissions, model boundaries and operating controls.
03Build working
Build working
increments.
You review functioning software against real data and evaluation sets every week.
04Deploy
Deploy
and harden.
We integrate identity, monitoring, security controls, runbooks and production support.
05Operate
Operate
and improve.
We monitor quality, cost and drift, then expand the system without losing control.
( 07 — SYSTEM ARCHITECTURES )
Discuss your system ↗Systems
we can
build.
07 / 08
ARCHITECTURE / 01PRIVATE KNOWLEDGE
01 / INPUTPRIVATE DATAPOLICIES
CONTRACTS
RECORDS
CONTRACTS
RECORDS
02 / CONTROLKNOWLEDGE LAYERACCESS
INDEX
RETRIEVAL
INDEX
RETRIEVAL
03 / OUTPUTCITED ANSWERPAGE
SOURCE
PERMISSION
SOURCE
PERMISSION
Private knowledge
system.
Policies, contracts and records with permission-aware retrieval and page-level citations.
Review this architecture ↗
ARCHITECTURE / 02CONTROLLED OPERATIONS
01 / EVENTBUSINESS STATESIGNAL
CONTEXT
OBJECTIVE
CONTEXT
OBJECTIVE
02 / POLICYPERMISSION GATERULES
RISK
HUMAN CHECK
RISK
HUMAN CHECK
03 / RESULTCONTROLLED ACTIONEXECUTE
ESCALATE
AUDIT
ESCALATE
AUDIT
Controlled operations
agent.
An agent that reads business state, proposes actions and executes only inside explicit permissions.
Review this architecture ↗Reference architectures. Scope, controls and measurable outcomes are defined for each engagement.
( 08 — ENGAGEMENT MODELS )
→Review.
Review.
Build.
Operate.
AI Transformation. Workflow portfolio, target architecture, operating model and phased delivery roadmap.
AI Regulation Readiness. A 5–10 day system inventory, role and risk map, control gaps and remediation plan.
Production Build. Architecture, product, integrations, evaluations and deployment.
Operate & Improve. Quality, cost and drift monitoring, support and expansion.
Have a system in mind?
Book a
system review.
In 30 minutes we will map the system boundary, critical dependencies and—where relevant—the regulatory controls a production path requires.
hello@n137.ai ↗