Methodology

Hyperion Physical AI Product System

An original methodology for leading Physical AI products through strategy, discovery, productization, launch and scale — five decision-gated stages evaluated through six lenses.

See the five stages in detail →

An original synthesis

The system is an original synthesis: product-management discipline joined with the engineering realities of machines that sense, decide and act — shaped by seventeen-plus years of connected-product and Physical AI work, and by executive education across product, innovation and platform design.

Hyperion's Physical AI Product System is an original methodology informed by executive education in end-to-end Product Management, customer-centred innovation, AI-product design, product-family architecture, and digital platforms through Kellogg Executive Education, UC Berkeley Executive Education, MIT xPRO, and MIT Professional Education.

Hyperion Consulting is independent and is not affiliated with or endorsed by these institutions.

How the method adapts

The stages and the lenses stay constant; depth and emphasis follow the client's situation.

A venture with a working prototype starts in Discovery — evidence before engineering expenditure.
An OEM business unit with several candidate product lines starts in Strategy — one thesis before requirements.
An integrator with repeat deliveries starts in Scale — separating the product from the projects.
A scale-up approaching launch starts in Launch — acceptance, support and operational readiness before revenue depends on them.

What the method produces

Every stage ends in artefacts a board, an investor or an operations team can act on:

Decision memoranda with a go, redirect, partner, pause or stop recommendation
Discovery evidence reports — customer, operator, field and economic
ConOps, product requirements and acceptance matrices
Launch and readiness scorecards with explicit gates
Product KPI trees and deployment-economics models
Capability transfer — the internal team ends stronger

An original synthesis

Hyperion Consulting is independent and is not affiliated with or endorsed by these institutions.

How the method adapts

The stages and the lenses stay constant; depth and emphasis follow the client's situation.

A venture with a working prototype starts in Discovery — evidence before engineering expenditure.

An OEM business unit with several candidate product lines starts in Strategy — one thesis before requirements.

An integrator with repeat deliveries starts in Scale — separating the product from the projects.

A scale-up approaching launch starts in Launch — acceptance, support and operational readiness before revenue depends on them.

What the method produces

Every stage ends in artefacts a board, an investor or an operations team can act on:

Decision memoranda with a go, redirect, partner, pause or stop recommendation

Discovery evidence reports — customer, operator, field and economic

ConOps, product requirements and acceptance matrices

Launch and readiness scorecards with explicit gates

Product KPI trees and deployment-economics models

Capability transfer — the internal team ends stronger