What is Concept-as-a-Service?

Concept-as-a-Service is a pay-on-acceptance model where Model T proactively generates hardware product concepts for engineering companies. Clients provide 5-7 target accounts, Model T selects the top 3 and delivers 2-3 validated product concepts per client — each with system architecture, BOM, and go-to-market angle — in 2 weeks. Payment only if at least one concept is accepted.

How does Model T work?

Model T uses a 6-stage AI-enhanced pipeline: Qualify (select top 3 from 5-7 accounts), Problem Map (OSINT research), Signal Research (market intelligence), Concept Engineering (architecture + BOM), Validate (expert feasibility review), and Deliver (client-ready package). Total ~50 hours per client, 1-2 weeks elapsed.

What is the cost of Model T?

From €15,000 per client engagement. Pay-on-acceptance: if zero concepts are accepted by the client, cost is zero. Approximately 60% of concepts have led to signed engineering projects.

What is Model T's conversion rate?

Model T achieved a 75% positive response rate during its validation roadshow across Munich and Switzerland — 7 meetings with zero negative reactions. Two meetings converted directly into signed projects.

Model T serves two audiences: semiconductor distributors and vendors who want proactive design-ins instead of reactive RFQ responses, and engineering or product companies who want validated concept exploration before committing R&D budget. Official vendor partners include Renesas, Lattice, NXP, STMicro, Infineon, and Qualcomm.

MODEL T — ANONYMIZED — 2 WEEKS — 6 STAGES

The Engine at Work

Human-operated AI pipeline — traced end to end.

Client names are anonymized. Methodology and outcomes are real.

VistaOptics Group — Cinema Equipment & Broadcast. ~50h of work across 2 weeks. Three validated product concepts delivered before the first meeting.

Anonymized engagement — client identity changed, methodology and outcomes are real.

Duration

2 weeks

Hours

~50h

Concepts

HUM decisions

WHAT THIS IS

Model T is not an automated system. It is a human-operated intelligence pipeline — the operator drives every decision while AI handles research aggregation, signal processing, and first-draft generation. At each HUM checkpoint below, you play the operator role.

HUM

Decides, validates, connects — every judgment call

Aggregates, drafts, scores — operates under direction

ANALYTICAL CHAIN — 6 STAGES — ~50h

01Company Intel3h

14 sources · 2 intelligence documents

A North American manufacturer of professional imaging hardware — cameras, lighting, and rental systems. ~$280M revenue, ~1,200 employees, operating for over 50 years. Holds 15+ industry technical awards. Four business units: Camera Systems, Lighting, Rental, and Solutions. Existing engineering relationship with the operator.

Revenue model: 100% one-time hardware sales — no software or subscription layer

Market signal: Hollywood production budgets down 22% in 2025

1,400+ professional clients globally: studios, broadcasters, rental houses

Core strengths: sensor design, color science, precision optics

> connecting to publi

02Problem Mapping4hHUM

11 candidates → 4 problems mapped

03Signal Research12hHUM

8 research docs · 47 signals · 2 selected insights

04Insight Selection8hHUM

ICE 24/30 · ICE 21/30 · 2 directions confirmed

05Concept Engineering15h

3 product concepts · 3 component BOMs · 3 roadmaps

06Engineering Validation8hHUM

3 concepts: engineering sign-off · 2 risk flags noted

All Case Studies