Infrastructure Profile

1–2% of 5-year infrastructure value8–12 weeks

How should we design AI infrastructure foundation?

Vendor-agnostic schema + API architecture for long-term context formalization.

What You Get

M
Maintenance
I
Integration
S
Structure
A
Accessibility
C
Capture
F
Formality
L0
L1
L2
L3
L4
L5
F
Knowledge Management
C
Business Process Management
S
Information Architecture
A
Enterprise Architecture
M
Data Governance
I
Systems Integration

Current infrastructure → target architecture across 6 dimensions

Context Assessment→Domain Modeling→Schema Design→Implementation Guide
  • Formal domain ontology (entities + relationships)
  • Vendor-agnostic schema design
  • API architecture + integration patterns

How We Assess

We design context architecture at the ontology level, not the vendor product level. This means defining entities, relationships, and constraints independent of any specific AI platform.

Architecture is vendor-agnostic by design. Works with any AI capability at the appropriate CMC level. No vendor lock-in.

Deliverable is implementation-ready: schema specifications, API design, integration patterns. Your dev team can build from this, or we can orchestrate build.

Process

Your time

12–15 hours (domain workshops + technical reviews)

Our turnaround

8–12 weeks

Weeks 1–3

Assessment + Domain Modeling

  • Context profile assessment
  • Domain ontology workshops
  • Entity and relationship mapping

Weeks 4–8

Architecture Design

  • Schema design (vendor-agnostic)
  • API architecture specification
  • Integration pattern design

Weeks 9–12

Documentation + Handoff

  • Implementation guide
  • Technical review sessions
  • Architecture presentation

Deliverables

Domain Ontology Map

Entities, relationships, constraints formally defined

Schema Design

Vendor-agnostic data model with versioning strategy

API Architecture

RESTful/GraphQL specifications for context access

Integration Patterns

How systems connect, event flows, data propagation

Implementation Guide

Tech stack recommendations, build sequence, vendor approach

Architecture Documentation

100+ page technical specification, implementation-ready

Architecture is reviewable by technical team. Specifications are implementation-ready.

Sample Output

Excerpt from sample architecture specification (Manufacturing, quality context layer)

Domain Ontology (excerpt)

Product SpecificationF → S

Fields

part_numberrevisiontolerances[]material_gradesurface_finish

Relationships

has_many: Inspection Records

belongs_to: Product Line

references: Supplier Qualifications

Inspection RecordC → M

Fields

record_idmeasurement_valuetolerance_refequipment_idoperatortimestamp

Relationships

belongs_to: Product Specification

measured_by: Equipment

triggers: NCR (if out-of-spec)

Supplier QualificationA → I

Fields

supplier_idcapability_scores[]audit_datecertification_statusapproved_parts[]

Relationships

qualifies_for: Product Specification

audited_by: Quality Team

syncs_to: ERP Vendor Master

API Specification (excerpt)

MethodEndpointPurposeDimension
GET/api/v1/specs/{part_number}Retrieve structured specificationA
GET/api/v1/specs/{id}/inspectionsInspection history for specA + I
POST/api/v1/inspectionsSubmit inspection recordC
GET/api/v1/suppliers/{id}/capabilitiesSupplier capability profileA + I
WS/ws/v1/quality-eventsReal-time quality event streamM + I

Integration Pattern: Event-Driven Quality Loop

Inspection submitted→Validation + enrichment→Quality event emitted→AI consumer processes

Vendor-agnostic. Works with any AI platform at CMC L3+. No vendor lock-in at the infrastructure level.

Pricing

1–2% of 5-year infrastructure value

Typical: $5–15M infrastructure investment over 5 years

Floor: $80,000

Range: $100,000 – $300,000

Additional factors that may adjust pricing:

  • •Infrastructure value (5-year horizon)
  • •Domain complexity
  • •Vendor abstraction requirements

Lower percentage due to larger magnitude, longer horizon