Operator-led · Governed AI transformation · Retail & F&B

Where opportunity grows from better decisions.

I don't sell you a bot. I install governed AI decision-making into the exact revenue bottleneck that's costing you — with the discipline of an operator who ran strategy and insight across 600 stores, not a slide deck.

What I Do

I install governed AI where the money is decided.

Three capabilities, one principle: AI acts on its own only inside explicit rules — and hands off to a human the moment a decision falls outside them. It fails safe, never silent. That's how you capture the upside of AI without the risk that stops most businesses from trusting it.

01

Decision Architecture

The models, automation, and governed decision engines behind how you operate — so choices are faster, evidence-grounded, and bounded by rules the AI can't override.

AI Transformation
02

Commercial Strategy

Turning market potential into revenue through disciplined pricing, promotion, and loyalty — growing the top line while protecting margin.

Retail & F&B Strategy
03

Product & Venture Building

Designing, validating, and building the systems you scale next — with a delivery team behind me — so you grow under constraint without betting blind.

Product Development

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Case Studies

Real systems, built and running.

Not concepts. Governed AI systems I designed and built end-to-end — each installed into a specific revenue bottleneck, with the row-level proof that it works. Clients anonymized under NDA.

Case 01

Same-day feedback recovery for a 600-store F&B retailer

NPS Automation600 storesn8n · Claude
Challenge

Customer feedback was reviewed in a weekly batch. By the time a detractor got a reply, they'd already churned — or posted the review publicly. Four agents spent the week sorting responses instead of saving customers.

What I built

An always-on workflow that treats every score as an event, not a report. The instant a score lands it's classified by sentiment and answered — detractors get an instant apology plus an internal alert, promoters a thank-you — with a human pulled in only where judgment matters. A live dashboard keeps leadership accountable without touching the automation.

Score lands webhook · real-time Classify sentiment Claude · 3-way route Detractor → apology + alert Neutral → logged Promoter → thank-you Live dashboard leadership view
7 days → min
Detractor response time
4 → 2
Agents needed for triage
~60 hrs
Saved per week
Case 02

Governed lead-to-booking for a two-tier tour operator

Quote-to-CashBounded AutonomySupabase · Claude
Challenge

Meta ads fed a WhatsApp funnel that leaked money in three places: leads went cold waiting for a reply; a hard trek and an easy sunrise sold from one funnel produced wrong-fit (and unsafe) bookings; and agents spent their time on tyre-kickers instead of buyers.

What I built

A governed quote-to-cash loop. An AI engine qualifies each lead against a written five-gate policy, then quotes, re-routes, or escalates — atomically holding a seat and emailing a payment link only on a clean match. A customer is never told they're booked until the money clears, and the never-oversold guarantee is enforced by a real database, not a spreadsheet.

Five-gate AI decision engine flow for lead-to-booking
The five-gate decision engine — acts in policy, escalates outside it.
~2.6×
Modelled contribution uplift, same ad spend
~0 min
First-response time, 24/7
16×
Lead-handling capacity per agent
Case 03

Automated competitor ad intelligence for a retail brand

Competitive IntelligenceWeekly · automatedStrategy loop
Challenge

Competitors' moves were read late, if at all. A metric would drop and nobody could say whether it was a competitive bleed or noise — so responses came weeks after the damage, when they came at all.

What I built

A weekly automated loop that pulls competitors' Meta ads, reads them like a strategist, and diagnoses why a metric moved — then proposes a same-week counter-move. The industry is incidental; the loop travels to any category where external signals move your numbers.

Automated competitor ad intelligence loop
External signal → your metric → diagnosis → response → result.
Weekly
Automated competitive read
Same week
Counter-move, not weeks late
Category-agnostic
The loop travels
Case 04

A governed content engine for retail & F&B marketing

Brand GovernanceHuman-in-the-loopn8n · Claude · Tavily
Challenge

Content demand outgrew the team and the agency retainer. Weekly promos across four channels meant briefing an agency, waiting days, three rounds of "that's not our voice," then scheduling — hours of coordination a customer never sees, and constant brand drift.

What I built

A brief goes in; a ready-to-post, on-brand promo comes out — researched against what's trending, then screened by a two-layer governor: hard deterministic rules it can't skip, plus an independent voice grader that's a different agent from the writer. Nothing publishes without one-click human approval.

Sample on-brand promo generated by the governed content engine
Sample output — brief to finished, brand-checked promo. Demonstration brand.
Days → min
Turnaround
100%
Brand-screened
1-click
Human approval

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About Me

Advice that's survived a real P&L.

Most AI and strategy consultants have never owned an operational decision. I have — for nearly a decade, at national scale, as Head of Insight & Strategy at Starbucks Indonesia.

01
Automated ~600 storesEliminated an hour of manual reporting per store — ~600 hours saved every day.
02
Shaped company, marketing & operation strategyBuilt the ROI discipline gating spend on trend, uplift, and cannibalization risk.
03
Architected pricing strategyGrounded in affordability, competitive data, and willingness-to-pay research.
04
Data, analytics & insight leadOwned data, analytics, and insight not only for Starbucks Indonesia but across other MAP Boga Adiperkasa portfolios.

Behind Ruang Tumbuh Inovasia is Arinta Wijaya, MBA. The name stays in its original language on purpose; the work speaks the language of global business: strong capability in strategy, Digital & AI Transformation, and measurable revenue.

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Let's Talk

Let's find what's holding your growth back.

We begin with your problem — not a pitch. A short conversation, and we'll find where the real leverage is. Then we shape the right way for me to help.

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