03 — Approach
Approach
03.1 — Disciplines
Disciplines
Lead generation
Demand, engineered end to end.
Acquisition is designed as a single instrumented system rather than a collection of campaigns: landing experiences, web and voice intake, validation, fraud scoring, CRM routing, consent certification and buyer delivery, each stage observable and each rejection explained.
AI automation
Intelligence, held to account.
Governed multi-model gateways that treat providers as interchangeable and policy as non-negotiable; self-auditing pipelines in which verification is a separate act from generation; and agent workflows with scoped permissions, resumable state and evidence required before any task is declared complete.
Operational software
Relational guarantees at the centre.
Partner portals, back offices and multilingual interfaces built on Postgres and typed services: constraints over conventions, migrations over mutations, and transactions that behave predictably precisely where they matter most.
Growth infrastructure
Marketing as a measured discipline.
Attribution plumbing, AI-assisted media production and lifecycle automation, designed by someone who answers personally for the funnel and therefore insists on knowing exactly how it performs.
03.2 — Method
Explicit boundaries. Deliberate control.
Applied AI most often fails at its boundaries: an unvalidated input, an unexamined output, a provider substitution that silently altered behaviour. The reference architecture Luis designs toward renders every boundary explicit, so that the model becomes one replaceable stage in a pipeline whose guarantees do not depend upon it.
Admit
A typed request envelope, an established identity and a declared intent.
Govern
Policy is evaluated before any model is addressed.
Route
Capability, cost and latency select the provider.
Validate
Output is checked against schema and domain invariants.
Attest
The decision and its evidence are written to an append-only trail.