Our approach
An engineering method, not prompt engineering.
We apply enterprise architecture disciplines to AI agents. Every deployment is traceable, governed, and built to last beyond the pilot.
Manifesto
AI Factory vs. amateur AI Lab.
The AI agent market suffers from a confusion: the apparent ease of prompt engineering is mistaken for the capacity to deliver a production system. A Notion + ChatGPT prototype is not an industrial agent. An undocumented n8n workflow is not an architecture.
GEOVTC applies to AI agents what TOGAF and SAFe brought to enterprise architecture and scaled agility: a method, deliverables, governance, and skills transfer.
Our clients don't pay for a chatbot. They pay for a system that executes, audits, maintains itself — and that they own.
Signature method
AI Agent Engineering in six phases.
An engineering discipline, not improvised prompt engineering. Each phase produces deliverables and a go/no-go decision.
- 01
Identification
Map high-leverage workflows — where an agent creates demonstrable value.
- 02
Definition
Business framing, golden rules, functional scope, measurable success criteria.
- 03
Representation
Skills · Memory · Context · Identity modelling (SMCI framework).
- 04
Specification
Target architecture, ERP/SaaS integration points, security, compliance.
- 05
Configuration
Parameters, operational prompts, guardrails, regression tests.
- 06
Instantiation
Deployment, monitoring, continuous improvement loop, ownership transfer.
Proprietary framework
SMCI — Skills · Memory · Context · Identity.
An AI agent is not a prompt. It's a system made of four dimensions we model explicitly before writing any code.
Skills
The agent's capabilities: actions, tools, integrations, queries. What it can do.
Memory
Its operational memory: histories, state, persistent knowledge. What it retains.
Context
The context received at each execution: business data, situation, constraints. What it knows when acting.
Identity
Its role, guardrails, tone, limits. What it is and what it refuses to do.
Governance
Compliance and auditability.
Three normative frameworks guide our deployments:
GDPR — minimization, anonymization, rights of individuals, processing registry
EU AI Act (2026) — risk classification, transparency, human oversight
ISO 27001 and ISO 42001 alignment — security and AI management
Roadmap 2027
Toward physical agents.
Pilot — 2027GEOVTC is gradually extending its AI Factory to the orchestration of physical agents: inspection drones, operational assistance robots, manipulation automata.
This scope addresses industrial, logistics and agricultural mid-market companies that combine digital workflows and field operations. Same SMCI engineering principles, same governance and sovereignty requirements. Pilot availability 2027 — first use cases scoped with a group of industrial partners.
Frequently asked questions
The vocabulary, clarified.
- What is an AI Factory?
- An AI Factory is an organisation and a method that industrialise the design, deployment and governance of AI agents — as opposed to an 'AI Lab' that produces prototypes. GEOVTC operates as an AI Factory: every AI agent is delivered as a product (specification, tests, monitoring, documentation, ownership transfer), with an engineering discipline inspired by TOGAF and SAFe.
- What is a multi-vendor AI agent strategy?
- A multi-vendor strategy means architecting AI agents across several platforms (Anthropic Claude, OpenAI, Moonshot Kimi, MiniMax, Nous Hermes) rather than depending on a single vendor. GEOVTC selects the platform per use case based on four criteria — capability, cost per task, sovereignty, resilience — through an abstraction layer that avoids vendor lock-in.
- What is the SMCI framework?
- SMCI (Skills, Memory, Context, Identity) is GEOVTC's proprietary framework for specifying an AI agent before any coding. Skills = its capabilities (tools, integrations); Memory = what it retains; Context = what is injected at each execution; Identity = its role, guardrails and limits. Modelling these four dimensions makes the agent predictable, testable, auditable and vendor-agnostic.
- What is Software 3.0?
- Software 3.0 (a term popularised by Andrej Karpathy) refers to systems driven by natural language and orchestrated by context: AI agents that reason, call tools and report. It succeeds Software 1.0 (human-written code) and Software 2.0 (trained models). GEOVTC industrialises the Software 2.0 → Software 3.0 transition for SMB operations.
- How much does an AI agent cost for an SMB?
- Cost depends on scope, but GEOVTC frames engagements as fixed-price: an AI Factory agent typically represents 6 to 12 weeks of work. ROI is measured in days freed per month (e.g. 4 days/month on a monthly close) and error reduction. The starting point is a free 45-minute audit that quantifies 3 priority use cases.
First step
45 minutes to map your 3 AI quick wins.
Free audit, no commitment. You walk away with a workflow map, 3 priority use cases, and an indicative valuation of the value at stake.