TTI × Midas Analytics
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TTI × Midas Analytics
Innovation & Product Development · An AI Use-Case Library

Every idea deserves
a thousand customers.

Your teams already find the spaces worth playing in. We add a library of AI use cases for the way TTI invents — opening with three: a synthetic audience, a concept visualizer, a business-case simulator.

use cases 01 · 02 · 03 · of a growing library live demo inside for Innovation & Product Dev 06 Jul 2026
Michele De Filippo
Prepared by Michele De Filippo, PhD
AI Lead · Midas Analytics
What we heard · how an idea travels at TTI

From a line on the master list
to a team in America.

01
The master list
Ideas pool in from every BU. One area lights up — "something in lighting."
02
Into the field
The team hits the market — talks to real users, walks the aisles.
03
Your own research
Back inside. Desk research shapes it into something concrete.
04
Hand-off to America
US lead teams pick it up and carry it to launch.
This is my understanding of your workflow — correct me where I'm wrong.
Where this engagement points

You already have the rarest ingredient — real contact with real users. We're not here to replace it. Just to give every step an AI gear.

Build TTI's library of AI use cases — one for every step an idea takes from the list to launch.

One use case at a time — small, concrete, judged on whether your team reaches for it. This deck opens with #01, #02, #03.

Agenda · the first three shelves of the library

Three use cases, mapped to your workflow.

Use Case 01

The Concept Visualizer

A one-paragraph brief becomes renders, iterations and marketing clips — before design or tooling spends a dollar.
10
iterations in one click
$0
of tooling spent to find out
Clips into③ Research↺ feeds UC 02
Use Case 02

The Synthetic Audience

✦ Alessandro's idea
Your customer base, recreated as AI personas. Every idea faces a thousand of them — and every one has an opinion.
1,000
opinions per run, in minutes
~$14
for a 1,000-person panel
Clips into② Field③ Research
Use Case 03

The Business-Case Simulator

A field winner leaves with a drafted business case — odds scored, risks flagged, assumptions from your own past launches.
min
from winner to draft case
×14
past cases behind each draft
Clips into④ Hand-off to America

②③④ = the workflow steps two slides back. All three are worked live in this deck.

The whole system · how the three tools connect

Together, they close a loop.

Before we open each tool, here's how they chain — an idea travels from a line on the master list to a drafted business case, mostly in one afternoon.

A
Write the brief
A line off the master list.
UC 01
See it
The visualizer renders it — in minutes.
UC 02
Hear 1,000 react
A thousand customers score what they see.
B
Refine & repeat
Fix the top objection. Loop back.
C
Field, with winners
Only survivors earn the trip.
UC 03
Draft the case
The business case, from past launches.

Brief in the morning, seen by lunch, a thousand reactions by the afternoon — field only the winners, and let them arrive with the business case already drafted. Now, each tool — worked live. →

Use Case 01 · The Concept Visualizer
01

See the product before it exists.

The friction
An idea stays words on a list. Nobody reacts honestly to a paragraph.
The fix
A brief becomes photoreal renders in minutes — something people can react to.
See it working · a real design session — it plays itself, click any step

From a paragraph to a product shoot.

visualizer.midasanalytics.ai · LINK-LIGHT design session
1
First render, from the brief
"Three magnetic panels, one battery, no tripod…" — hmm. Too boxy.
2
Change the design
"Round the edges, soften the face." — too friendly now.
3
Change it again
"Keep the rugged frame, slim it down." — that's the one.
4
10 iterations, one click
Sizes, mounts, add-ons — the whole family, while the coffee is still warm.
5
Pick 3 colorways
Black/red, olive, grey — off to the marketing shoot →
First AI render — boxy draft✕  rejected — too boxy
Second AI render — soft consumer draft✕  rejected — too soft
Third AI render — picked✓  picked
Iteration: compactcompact
Iteration: XL twinXL twin
Iteration: kickstandkickstand
Iteration: carabinercarabiner
Iteration: tripodtripod
Iteration: bumpersbumpers
Iteration: corner linkcorner link
Iteration: diffuserdiffuser
Iteration: pen lightpen light
Iteration: swivel mountswivel
Colorway: black/redblack / red
Colorway: oliveolive
Colorway: greygrey
Every image is AI-generated — from the brief on the left, no designer hours. Same concept the panel just scored.
…and the marketing shoot · same afternoon

Three colorways picked. Three clips, rolling.

AI-generated black / red
AI-generated olive
AI-generated grey
AI-generated from the colorway stills — illustrative of pace, not final creative. Master-list line to footage in one afternoon.
See it working · one concept, a whole campaign

One brief. A campaign's worth of shots.

Studio hero campaign shot
Studio hero· editorial
Jobsite campaign shot
On the jobsite· blue hour
Workshop lifestyle campaign shot
Workshop lifestyle· golden hour
Macro detail campaign shot
Macro detail· the magnetic edge
In-use renovation campaign shot
In use — renovation· lifestyle
Exploded view campaign shot
Exploded view· the modularity
In-context garage shot
In context — garage· on the shelf
Colorway board
Colorways· one prompt, three finishes
AI-generated 8 shots · 1 brief
Every frame AI-generated from one paragraph — studio, jobsite, macro, lifestyle. A whole campaign before a photographer is booked.
Use Case 02 · The Synthetic Audience
02

A Kickstarter simulator, populated by your customers.

The friction
Field testing costs weeks and budget — only a handful of ideas get tested.
The fix
A thousand AI personas of your customers. Post a concept, watch who backs it.
Sparked by Alessandro in our working session.
How a synthetic customer is built

Three layers make a persona believable.

Layer 1 · Demographics
Sampled from your base
Age, income, trade, region — mirroring your real customer mix, not invented.
Layer 2 · Mindset
Habits & brand life
What they own, where they shop, how they buy. A platform-loyal pro reasons differently from a weekend renovator.
Layer 3 · Reasoning engine
A model matched to the mind
A model matched to the mind — a gut-take shopper on a fast model, a spec-weighing electrician on a frontier one.
Demo segments· Pro tradesperson Serious DIYer Casual homeowner — real segments come from your base.
What changes · and what deliberately doesn't

Today, testing is the scarce resource.

Today — a few ideas get heard
Master list
every BU's ideas
weeks & budget per test
Field research
a precious few
Fieldwork is superb but expensive and slow — so it rations which ideas get tested. The rest wait their turn on the list.
With the synthetic audience
Master list
every idea
all of it
Synthetic panelminutes per idea
winners only
Field research
unchanged — earned
Every idea faces the panel first. Your fieldwork doesn't shrink — it sharpens: the trips you take are spent only on ideas that earned them.
See it working · it runs itself — click anything to take over

Ten customers. Then a hundred, a thousand — then a million.

panel.midasanalytics.ai · TTI synthetic audience
Concept: Audience: Panel:
10 personasest.43k tokensUS$0.66~1 min
Sampling personas…
0 / 0 responded
would buy 0on the fence 0pass 0
0
panel score
GO
panel of 1,000 · stable signal
—
would buy
—
price they'd pay
Positive reaction by segment
Pro tradesperson
—
Serious DIYer
—
Casual homeowner
—
Loved most
Top objection
Suggested next step
This run ·10 personas·43k tokens·US$0.66·1m 12s
Illustrative — invented products & customers. The real panel runs on TTI's actual data.
The economics · nothing hidden

Every run shows its price — before you press run.

PanelMixTokensEst. costWall-time
10 personasquick pulse · mirror the base≈ 43k≈ US$0.14~1 min
100 personasmirror the base≈ 428k≈ US$1.40~2 min
1,000 personasmirror the base · stable signal≈ 4.28M≈ US$14~11 min
1,000,000 personasyour whole base · census-grade≈ 4.28B≈ US$14,400~overnight
The same read, the traditional way
One focus group (8–12 people)US$6–12k · 4–6 wks
Concept survey (n=250)US$15–30k · 3–8 wks
The panel doesn't replace these — it decides which ideas deserve them.
The model lanes · Casual → Gemini 2.5 Flash · Haiku ≈ $0.002/persona Serious DIY → Sonnet · Kimi K2.7 ≈ $0.01 Pro → Opus · Gemini 3 ≈ $0.05

Illustrative, at public list prices — the app shows your exact figure before each run. Each persona runs on the cheapest model that holds its character. Traditional-research costs are typical market ranges.

Read this slide before believing the last one

A signal, not an oracle.

It ranks, it doesn't decide
Directional — it sorts fifty ideas into pursue / refine / park. It won't promise a launch succeeds. Humans keep the final word.
Calibrated against your history
We backtest against products you've already launched — scores checked against what actually happened.
The field stays sacred
Winners still go to real users. We'd never automate the field — the panel just makes every trip worth taking.
Use Case 03 · The Business-Case Simulator
03

The business case, drafted before the meeting.

The friction
A winner needs a business case — weeks of spreadsheet archaeology.
The fix
AI drafts v1 in minutes from your past cases — odds scored, risks flagged.
See it working · change an assumption, watch the case redraw

One draft. Every number has a source.

case.midasanalytics.ai · business-case simulator
AreaMax 2200 — a past TTI work-light launch
Closest past launch
AreaMax 2200
launched 2022 · 210k units in year 1
learns fromto draft
Now drafting · new concept
LINK-LIGHT
modular panel work light (never launched)
LINK-LIGHT · draft business casev0.1 · auto-filled from AreaMax 2200 + 13 more
Assumptions — auto-filled from past launches · editable
Retail price (MSRP) $99
Unit cost (COGS) · from 3 closest bills of materials$34
Retailer margin38%
Year-1 volume 120k units
Tooling & certification$850k
Launch marketing$600k
Returns rate3%
The case, computed live
Net revenue / unit$61.40
Contribution / unit$25.60
Year-1 net revenue$7.37M
Year-1 contribution$3.07M
Fixed cost to launch$1.45M
Year-1 operating contribution+$1.62M
Breakeven volume~57k units
72
/ 100
Odds of success
A launchable case at $99.
Scored against 14 past launches · nearest: AreaMax 2200 (2022).
Risks flagged
Price sits $20 above incumbent tripod lights — elasticity risk the panel already flagged.
Magnet supplier is single-source in year 1 — dual-source before scale.
Panel signal strongest with serious DIYers (82%) — channel mix should follow.
Drafted in 4 min · every cell carries its source — hover to see which past launch.
Illustrative — AreaMax 2200 and LINK-LIGHT are invented. The real tool drafts from your actual past launches, wins and misses alike.
The library · where this deck leaves you

Three shelves, filled.

Each clips into one workflow step — fast to ship, useful enough to stay. The library compounds: shared data, one login. The next shelves, we fill together.

01
The Concept Visualizer
Brief → renders → 10 iterations → marketing clips — before design or tooling spends a dollar.
this deck · ships first
02
The Synthetic Audience
A thousand customer opinions on any idea, in minutes — with a price tag on every run. Alessandro's idea.
this deck · feeds on 01
03
The Business-Case Simulator
Field winners leave with a drafted case — odds scored, risks flagged, every number sourced from your past launches.
this deck · closes the journey
How we'd start · light on your calendar

Three steps to a live panel.

Step 01

Walk the demo

We run this simulator live with your team and choose the segments that matter.

Step 02

NDA & scope

An NDA to see your customers, then a light statement of work — about a week.

Step 03

Build & calibrate

First panel on your real segments, backtested on a past launch — the first score comes with receipts.

The payoff · your innovation process, reinvented

See it. Hear it. Bank it — before you build it.

Visualize the concept
Use Case 01
Concept render
In-use render
Colorways
AI-generated
See it — concepts as images & film, in minutes.
Validate with customers
Use Case 02
DW
Dana Whitfield
34 · Electrician · Pro
"Detach a panel, stick it to the stud, aim it. Sold."
PN
Priya Nair
45 · Serious DIYer
"Love it at $99. Not at $129."
RA
Rita Alvarez
29 · First-home owner
"I'd borrow my dad's before spending $129 on one."
MO
Marcus Osei
41 · Weekend renovator
"One under the sink, one in the attic — solves a real annoyance."
1 of 1,000
Hear it — a thousand customers, each with an opinion.
Value the business case
Use Case 03
GO · validate in field
LINK-LIGHT
+$1.6MYear-1 operating contribution · 72% odds
Panel score 74 · strongest with serious DIYers.
PARK · parity, not edge
Self-Rinse Vac
−$0.4MYear-1 operating contribution · 33% odds
Panel score 51 · three brands already promise it.
REFINE · pro lane only
Stack-Hub
+$0.7MYear-1 operating contribution · 55% odds
Panel score 62 · cut weight before you cut price.
Bank it — the case, positive or negative, up front.

A line on the master list becomes a launch decision — renders, a thousand opinions, and a costed business case — before a dollar of tooling is spent.

TTI × Midas Analytics
Who's behind this · Midas Analytics

We're builders. AI is our bread and butter.

Since the '90s internet wave, we've turned each new technology into business growth. Today that's AI — from use-cases to prototyping, testing and implementation in weeks, not months.

We build our own product
We run the #1 AI market-intelligence platform in Asia. When we advise, it's from the trenches — not a textbook.
Senior pairs, no juniors
An AI + Data expert in your boardroom — the people who ship, weekly, all the way through.
Vendor-independent
Tied to no single tool — genuinely unbiased recommendations, with partners worldwide.
You own the outcome
The software and the knowledge stay with you — we co-build, we don't lock you in.
What we do · three ways in

Learn it. Map it. Build it.

Service 01
AI Courses
Hands-on upskilling that takes a team from hyped to building — the #UnleashingAI Program, for communities and inside enterprises.
You walk away withA fluent team + a 90-day adoption plan.
Service 02
AI Discovery
A senior AI + Data pair embeds — 4 weeks, fixed fee — to answer where to play & how to win, and leaves a costed, owner-mapped roadmap.
You walk away withA board-ready plan you can fund.
Service 03 · this deck
AI Product Builds
We ship production AI tools — chatbots, apps, data foundations — co-built on your real inputs, so the software and the knowledge stay with you.
You walk away withWorking tools you own.

Start anywhere — most teams learn, then discover, then build. The three use cases in this deck are AI Product Builds.

Case study · AI Product Builds
Precision-manufacturing equipment · two production tools, shipped & owned in-house

Repetitive service work, handed to AI.

The challenge
A global maker of precision manufacturing machines. After every install, the technical team drowned in repetitive service questions — and customer health was tracked by hand, so follow-ups quietly slipped.
What we built
  • A customer servicing chatbot that answers only from each machine's own manual — deflecting the bulk of basic inquiries, 24/7.
  • A bi-weekly customer report app: an export from their ERP becomes a status + delta report, with a next action per customer.
The outcome
~70%
of repetitive inquiries deflected, around the clock
0
follow-ups dropped — every customer reviewed each cycle
Industry shown; client identity withheld. Both tools — and the knowledge — delivered in-house.
Case study · AI Discovery
Sustainability engineering consultancy · 4-week discovery → a costed transformation roadmap

From "AI everywhere" to a funded plan.

The challenge
A ~50-engineer green-building consultancy across several countries. The CEO wanted AI embedded everywhere — but only two people were AI-proficient, the tool stack sprawled across 11 entities, and there was no shared map of where AI creates value first.
What we did
  • Scored opportunity sheets across every function — ranked by value and effort.
  • Live, throwaway proofs-of-concept on their real data — an agent against 300+ active projects.
  • A central-dashboard architecture + a sequenced 6–12 month plan with owners, dependencies and ROI.
The outcome
4 wks
to a board-ready, costed roadmap they could fund
1
shared map — where to start, who owns it, what it returns
Industry shown; client identity withheld. The plan — and the knowledge — stay with the client.
TTI × Midas Analytics

Thank you.

A library of AI use cases for the way TTI invents — opened by giving every idea a thousand customers.

midasanalytics.ai
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