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EMPV / AI LAB

AI Lab: turning hypotheses into verifiable systems.

Research directions and prototypes used to test which AI ideas hold up technically, operationally and as products.

A
Research / systems intelligence

System Twin

What we are testingCan we reconstruct what a system does without conflating observed facts, declarations, derivations and inferences?
Repository state

Research / model-definition · schema and stack not frozen

Current focus

Cross-source identity · evidence · time · reconciliation · projection

B
Applied R&D / local AI

Local AI

What we are testingHow do we prove what a local model can do before assigning it production tasks?
Repository state

Public Core 0.3.1 RC1 · schema 1.0.1

Current focus

discover → candidate → TEST → preflight → one-RUN authorization → bounded RUN → evidence → compare

C
MVP / agent orchestration

Opportunity Engine

What we are testingDoes starting from problems instead of company lists produce prospects that human reviewers can qualify with stronger evidence?
Repository state

Current milestone: Problem Research → Prospect Research → Qualification

Current focus

Evidence ≠ interpretation ≠ hypothesis · human gate for external actions

D
Product direction / vertical SaaS

Vertical Operations

What we are testingHow much of the operating model can be reused across other verticals without turning it into a generic management system?
Repository state

First complete vertical built around pet hospitality

Current focus

Booking → capacity → service → staff work · one operating domain

E
Research / epistemic AI

Trustworthy Reasoning

What we are testingCan we build a defensible scientific project around reasoning, abstraction and planning that preserves the history of evidence?
Repository state

Phase 0 — Call decomposition and research governance

Current focus

No novelty claim validated · evidence graphs · bitemporal knowledge · epistemic branching