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.

PROCESS BLUEPRINT

Magic Flow

Six stages. 20 steps. ~2 weeks from lead to signed project. Every step is documented, every hand-off is defined.

6Companies Processed

32+Insights Synthesized

13+Concepts Created

17%Meeting Conversion

Stage 1

QUALIFICATION

SLA: 5h

Lead Qualification

Sales Manager↓

Sales Manager evaluates the incoming lead against ICP criteria: revenue range, headcount, engineering capability, geographic fit, and strategic alignment with Promwad services.

INPUT

CRM lead data

Company website

LinkedIn profile

Industry reports

OUTPUT

Qualified lead record

Initial company brief

TOOLS

CRMLinkedIn Sales NavigatorGoogle Search

Create Planner Task

Project Lead↓

Project Lead creates a structured planner task, assigns the research team, sets deadlines, and ensures the 8-folder project structure is initialized.

INPUT

Qualified lead record

Initial company brief

OUTPUT

Planner task in project tracker

Assigned team resources

TOOLS

FiberyGitHub

Go/No-Go Decision

◆ Project Lead↓

Project Lead uses AI to draft initial.md and project_desc.md with company summary, engagement rationale, and risk assessment. Reviews output and makes the final GO/NO-GO decision. On GO, the full 8-folder structure is generated.

INPUT

Qualified lead record

Market context

Resource availability

OUTPUT

initial.md

project_desc.md

8-folder project structure

TOOLS

ClaudeInternal templatesGitHub

GO → Stage 2NO-GO → Archive

0companies qualified

Stage 2

INSIGHTS

SLA: 16h

Company Profile Analysis

◆ Product Analyst↓

Product Analyst uses AI to conduct deep OSINT research: financials, org structure, tech stack, competitors, and key decision-makers. Reviews and validates structured profiles for accuracy and completeness.

INPUT

initial.md

project_desc.md

Public company data

OUTPUT

company_profile_*.md

deep_general.md

deep_competitors.md

deep_key_persons.md

TOOLS

PerplexityClaudeLinkedInGoogle

Product Insights Generation

◆ Product Analyst↓

Product Analyst uses AI to generate 5–7 product insight hypotheses, each scored by ICE (Impact, Confidence, Ease). Maps client pain points to Promwad engineering capabilities. Validates relevance and market fit.

INPUT

company_profile_*.md

deep_general.md

Technical capabilities matrix

OUTPUT

product_insights_*.md (5–7 insights with ICE scores)

TOOLS

ClaudePerplexityInternal knowledge base

Technical Review

◆ Technical Expert↓

Technical Expert uses AI to evaluate each insight for feasibility: BOM estimation, development complexity, required competencies, and risk factors. Validates against real-world project experience.

INPUT

product_insights_*.md

Promwad tech stack reference

OUTPUT

technical_review_*.md

TOOLS

ClaudeInternal engineering wikiDatasheets

0+product insights synthesized

Stage 3

PRODUCT CONCEPTS

SLA: 18h

Select 2 Best Insights

◆ Product Strategist↓

Product Strategist uses AI to rank insights by combined ICE score, strategic fit, and technical feasibility. Selects the top 2 insights for deep-dive concept development. Confirms selection with stakeholders.

INPUT

product_insights_*.md

technical_review_*.md

ICE scores

OUTPUT

Selected insight pair

Selection rationale document

TOOLS

ClaudeScoring matrix

Deep Analysis × 2

◆ Product Analyst↓

Product Analyst uses AI to conduct deep market analysis for each insight: TAM/SAM/SOM sizing, competitive landscape, regulatory considerations, and technology readiness. Enriches with domain-specific context.

INPUT

2 selected insights

Market data

Competitor landscape

OUTPUT

*_deep_analysis.md × 2

TOOLS

ClaudePerplexityGoogle ScholarPatent databases

Create Product Concepts × 2

◆ Product Manager↓

Product Manager uses AI to draft full product concepts: value proposition, feature set, architecture overview, go-to-market sketch, revenue model, and development roadmap. Shapes narrative and validates business assumptions.

INPUT

*_deep_analysis.md × 2

Promwad capabilities matrix

OUTPUT

*_product_concept.md × 2

TOOLS

ClaudeFigma (wireframes)Internal templates

Validate + Business Logic

◆ Product Manager↓

Product Manager uses AI to stress-test each concept: unit economics, pricing strategy, competitive moat, and risk matrix. Runs internal review with engineering and sales leads to confirm viability.

INPUT

*_product_concept.md × 2

Financial models

OUTPUT

Validated concepts with business cases

TOOLS

ClaudeSpreadsheet modelsInternal review board

Expert Validation

1+1h

◆ Technical Expert + Sales Lead↓

Technical Expert uses AI to review architecture feasibility, then Sales Lead uses AI to evaluate market positioning and objection handling. Both experts sign off on their respective domains.

INPUT

Validated concepts

Technical architecture drafts

OUTPUT

Expert validation reports

Risk assessments

TOOLS

ClaudeInternal review workflowVideo call

Finalize Concepts

◆ Product Manager↓

Product Manager uses AI to consolidate all feedback, resolve conflicts, and produce final concept documents with executive summary. README.md captures the full decision trail and artifact index.

INPUT

Expert validation reports

All concept documents

OUTPUT

Approved concepts

README.md

TOOLS

ClaudeGitHubInternal templates

0+product concepts created

Stage 4

MINI-OFFER

SLA: 7h

Create Mini-Offer + Sales Script

◆ Product Strategist↓

Product Strategist uses AI to craft a concise mini-offer tailored to the client’s pain points and a detailed sales script with talk tracks, objection handling, and meeting flow. Personalizes tone and emphasis.

INPUT

Approved concepts

Client profile

Sales playbook

OUTPUT

mini_offer.md

sales_script.md

Objection handling guide

TOOLS

ClaudeInternal sales templatesCRM data

Marketing Brief

Product Manager → Marketing↓

Product Manager translates the mini-offer into a marketing brief with key messages, visual direction, and slide structure. Handed off to Marketing Specialist for presentation creation.

INPUT

mini_offer.md

Brand guidelines

Client context

OUTPUT

marketing_brief.md

Visual direction notes

TOOLS

FiberyBrand asset library

Create Presentation

Marketing Specialist↓

Marketing Specialist designs a polished client-facing presentation: problem framing, concept showcase, technical credibility, and clear next steps. Includes a leave-behind one-pager for post-meeting circulation.

INPUT

marketing_brief.md

Brand templates

Product visuals

OUTPUT

Client presentation (PDF/PPTX)

Leave-behind one-pager

TOOLS

FigmaPowerPointCanva

Quality Check + Library

◆ Product Manager↓

Product Manager uses AI to run a quality checklist: factual accuracy, brand consistency, message alignment, and competitive positioning. Approves materials and indexes them in the company knowledge library.

INPUT

Client presentation

mini_offer.md

Quality checklist

OUTPUT

Approved presentation

Library entry

Go-to-present sign-off

TOOLS

ClaudeInternal QA checklistAsset library

0+presentations delivered

Stage 5

CLIENT SIDE

SLA: 4h

Conduct Client Meeting

Sales Manager↓

Sales Manager presents the mini-offer and product concepts to client stakeholders. Follows the sales script while adapting to live feedback. Captures reactions, questions, and next-step signals.

INPUT

Client presentation

sales_script.md

Objection handling guide

OUTPUT

Meeting recording

Real-time notes

Client feedback

TOOLS

Zoom/TeamsMeeting recorderCRM

Meeting Protocol

Sales Manager↓

Sales Manager documents meeting outcomes: key decisions, client sentiment, objections raised, and agreed next steps. Updates CRM with deal stage and triggers the appropriate follow-up workflow.

INPUT

Meeting recording

Real-time notes

Client feedback

OUTPUT

meeting_protocol.md

Follow-up action items

CRM status update

TOOLS

FiberyCRMEmail

GO → Pilot ProposalMAYBE → Follow-upNO-GO → Lessons Learned

0%positive meeting outcome

Stage 6

HANDOFF

SLA: 4h

Engineering Handoff Package

◆ Engineering Lead↓

Engineering Lead assembles the handoff package for accepted concepts: technical brief with architecture details, preliminary project scope with milestones, and resource/timeline estimate. This bridges the gap between concept acceptance and project kickoff.

INPUT

Accepted concepts

Meeting protocol

Client feedback

OUTPUT

Technical brief

Preliminary project scope

Resource estimate

TOOLS

FiberyConfluenceTemplates

Pipeline Update & Retrospective

◆ Pipeline Manager↓

Pipeline Manager updates the dashboard with final outcomes: which concepts were accepted, rejected, or deferred. Documents lessons learned for process improvement. Identifies follow-up opportunities and seeds the next round of targets.

INPUT

Meeting outcomes

Concept acceptance data

Client signals

OUTPUT

Pipeline dashboard update

Lessons learned

Next-round targets

TOOLS

CRMFiberyAnalytics

0%concepts → signed projects

Ready to Run the Pipeline?

Let us run the Magic Flow for your target accounts and deliver validated product concepts in ~2 weeks.

START PILOT