Models

Model your business once. Build everything on it.

AML is a privately-owned, CMOF-compliant (ISO/IEC 19508) metamodel at level M2 that ageni is built using. It unifies lexicology, modelology, and metrology into one gateway so agents can model, predict, and version M1 architectures — architectures forced to adopt the combined constraints of every ageni engine, with every resulting feature traceable to a company's universal profit stream, revenue stream, and value stream.

Every number means one thing, on every report.

AMM is the Universal Measure Model: it forces every business number onto a base alphabet of SMM-typed measures and a KPI tree grounded in FIBO, so two derivations of the same quantity always fold to one identity.

Predict the biggest opportunity before any survey runs.

AOPM is the predictive engine that operationalizes Outcome-Driven Innovation. It reads each gate's rate gap versus its sector benchmark off the APSM matrix, measured through AMM, ranks the automation queue, and paints a CostToOptimize colour on every cell. The opportunity is on screen before the first survey is ever run.

One clear picture of where your profit comes from.

APSM enforces, for every sector-coordinate (NAICS + SIC + GICS fused), an SBVR vocabulary that causally binds every concept, association, and event to one position in the universal profit stream — so what an enterprise sells (revenue streams) and delivers (value streams) traces to a single source of truth.

Keep your data clean as your team grows.

ATGM is the ROOT of ageni's naming convention. It enforces suffix and name rules that bind word-form types to metaclasses — making it impossible to model a concept from its surface word-form alone; every type resolves through SBVR concepts, facts, roles, and formulations.

Catch a broken rule the moment it's written.

AVST performs Virtual Node Generation — projecting expression into natural and formal languages by extending a language's own grammar to enforce enterprise-specific constraints on any node in the tree.