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.

AeroValve Industries — Industrial Pneumatics & Fluid Power. ~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

12 sources · 2 intelligence documents

A Central European manufacturer of industrial pneumatic actuators, valves, and air preparation units. ~350 employees, 40+ years in business, ~€80M revenue. Core clients: automotive assembly lines, packaging machinery, food & beverage. Facing commoditization pressure from Asian manufacturers.

90% of revenue from standard catalog products — no IoT or digital service layer

Distributors control 70% of sales channel — limited direct OEM relationships

Core competence: pneumatic actuation and air preparation — deep domain, narrow offering

No recurring revenue — purely transactional hardware sales model

> connecting to publi

02Problem Mapping4hHUM

8 candidates → 4 problems mapped

03Signal Research12hHUM

5 research docs · 32 signals · 3 market directions

04Insight Selection8hHUM

4 insights scored · ICE 25/30, 23/30, 20/30 · 1 rejected

05Concept Engineering15h

3 product concepts · 3 component BOMs · phased roadmaps

06Engineering Validation8hHUM

3 concepts: engineering sign-off

All Case Studies