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Selected Advisory Work

Strategy applied
in the real world.

Advisory engagements where structural diagnosis, market repositioning and platform strategy moved the needle — documented from the inside.

The engagements
behind the framework

These are real advisory projects — not anonymized hypotheticals. Each one informed a specific dimension of the G.E.A.R. model. The structural patterns that emerged across both engagements are what this consulting practice is built on.

Case Study 01

From payment reconciliation tool
to data governance platform

Revenue + Architecture 2025 — Ongoing Data Governance SaaS · Southern Europe

The Situation

The client was a technically strong automated financial reconciliation platform, built and launched in Uruguay, that had developed genuine traction with payment-adjacent companies in the local market. The founding team wanted to expand into Spain and Europe — a significantly larger, more regulated and more competitive market.

The challenge wasn't the product itself. The platform processed up to 1,000 transactions per second, had over 300 active users and was handling more than 16M monthly transactions with 95%+ automated reconciliation rates. The challenge was structural: the platform was positioned as a bank reconciliation tool in a market full of accounting software and ERPs doing basic reconciliation as a feature.

Entering Spain with that positioning meant competing on price with entrenched generic solutions — a race to the bottom that would have destroyed the margin the product deserved.

The Structural Diagnosis

The G.E.A.R. diagnostic identified two compounding structural gaps:

Revenue gap: The platform was priced and packaged as a reconciliation utility when it was operating as data infrastructure for its best clients — managing data lineage, transformation, enrichment, governance workflows and real-time discrepancy alerting well beyond what any ERP offered. The value delivered significantly exceeded the value claimed.

Architecture gap: The platform narrative led with the reconciliation use case — which triggered a comparison with tools designed for accountants. The actual architecture (any-data ingestion, no-code governance, multi-company/multi-currency, 1,000 TPS) positioned the platform firmly as a data operations layer — but that story wasn't being told.

The Intervention: Three Phases

01
Spanish Market Entry Analysis Full mapping of the Spanish payment ecosystem: PSPs, payment orchestrators, acquiring banks, e-commerce operators and mid-market financial services. Identified PSPs and orchestrators as the primary segment — the only buyers that experienced the reconciliation pain at the scale the platform was built to serve, and where regulatory pressure (PSD2/PISP/AISP) created an active compliance need beyond basic accounting.
02
Regulatory Positioning Research Deep research into PSD2, PISP and AISP regulatory requirements for Spanish payment providers. Identified the compliance burden these companies carried and built a positioning bridge — the platform as the operational layer that makes regulatory data obligations manageable and auditable, not just a reconciliation tool. Engaged 8+ payment providers in Spain to validate the positioning before formalizing the GTM.
03
Strategic Pivot: Reconciliation → Data Governance Designed and led the strategic repositioning from a reconciliation SaaS to a full data governance platform — incorporating the capabilities the platform already had (lineage visibility, enrichment, transformation, governance automation) into a new product narrative. This was not a product rebuild — it was a structural re-framing of existing capabilities into a higher-value category. TAM expansion estimated at 3.2× the original reconciliation market. Simultaneously designed the Q1–Q3 2025 AI/ML product roadmap using RICE/WSJF prioritization, with projected 40% customer retention increase.

What This Engagement Reflects

This engagement is a live example of the Revenue and Architecture dimensions of G.E.A.R. working in tandem. The product was strong — the structural gap was in how that strength was communicated, packaged and targeted. The intervention didn't change the product. It changed the frame.

3.2×
TAM Expansion via Repositioning
+40%
Projected Retention Increase
8+
Spanish PSPs Engaged in Validation
90%
AI/ML Roadmap Execution Rate
Structural Insight

"The most dangerous position for a strong product is a weak category. The platform was solving a data operations problem while being perceived as an accounting utility. The intervention was to realign the narrative with the actual problem being solved — and the buyer who experienced it most acutely."

GTM StrategyMarket Entry SpainPSD2 / PISP / AISPRevenue ArchitecturePlatform PositioningData GovernanceProduct RoadmapRICE / WSJF
Case Study 02

Web3 architecture for a
Gen-Z narrative platform

Architecture + Expansion Sep 2025 Web3 · Consumer Platform · Design Sprint

The Situation

The client came to me as an independent Tech Advisor with a compelling creative concept — a collaborative narrative platform built around the "6 words" format (inspired by Hemingway, Monterroso and Wired's editorial tradition), designed for Generation Z users aged 17–28.

The founding team had a strong cultural insight and a clear target audience. What they needed was a structured approach to validate the concept before committing significant technical resources — and a technology architecture recommendation that balanced Web3 ambitions with MVP pragmatism.

The structural challenge was common in early-stage Web3 consumer products: the technical vision (blockchain-native, token-incentivized participation) was significantly more complex than the validation stage warranted. Building for the end state before validating the core engagement hypothesis would create technical debt and slow the critical early feedback loops.

The Design Sprint

I designed and facilitated a 5-day Design Sprint (September 8–12, 2025) to validate the core engagement hypothesis and define the MVP scope before any significant technical investment.

The sprint produced three critical outputs: a validated user engagement hypothesis (the "6 words" format resonated strongly with Gen Z testers, producing near-unanimous stated intent to engage), a clear identification of the execution gaps (UX confusion, broken onboarding flow, visual monotony) that needed resolving before any scaling, and an updated probability assessment — concept validation at 90%, 30-day retention potential revised upward to 65% with UX fixes applied.

The testing also confirmed one non-obvious finding: the platform's social purpose dimension — enabling creative participation around cultural references — resonated more strongly with the Gen Z testers than the gamification or monetization mechanics. This was a positioning insight that needed to lead the product narrative.

Technology Architecture Recommendation

Based on the sprint findings, I delivered a formal MVP Technology Advisory document with a phased architecture designed to validate fast and scale when earned — not before.

Phase 1
Core MVP — Weeks 1–3 Next.js 14+ / TypeScript frontend, Node.js backend, PostgreSQL + Redis, Vercel + Railway deployment. No blockchain in Phase 1. Focus: the "6 words" experience, basic drops, social sharing and likes. Rationale: validate engagement before adding Web3 complexity. Estimated build: 2–3 weeks.
Phase 2
Social Layer — Weeks 3–4 Conditional on Phase 1 validation data. Functional user profiles, community feed, discovery mechanics, gamification layer (achievements, streaks), full mobile optimization. This is where retention mechanics are built if engagement data warrants investment.
Phase 3
Web3 Integration — Weeks 5–8 (if validated) Polygon (MATIC) integration for low-cost NFT mechanics, curator system for narrative evolution, AI-generated audio/visual elements, blockchain-native ownership of contributed narratives. Only triggered if retention metrics from Phase 1–2 justify the architectural complexity.

The Structural Principle Applied

The advisory intervention here was an Architecture dimension problem: the founding team's natural instinct was to build toward their end-state vision. The structural recommendation was to decouple the validation architecture from the production architecture — and only bridge to Web3 when the engagement data made it structurally justified, not aspirationally motivated.

This is the difference between building infrastructure for a platform that exists and building infrastructure for a platform you hope will exist.

90%
Concept Validation Score (Sprint Testing)
65%
Projected 30-Day Retention Post-UX Fix
5 days
Design Sprint Duration
3 phases
Phased Architecture Delivered
Structural Insight

"Web3 features are architecture decisions, not product decisions. Building them before the engagement hypothesis is validated inverts the risk profile — you're committing to infrastructure complexity before you know if the core experience warrants it. The recommendation was to earn the blockchain layer through validation data, not assume it."

Web3 ArchitectureMVP StrategyDesign Sprint FacilitationPolygon / NFTsGen Z Product DesignNext.js StackTechnical AdvisoryConsumer Platform

How every advisory
engagement works

01

Structural Diagnosis First

Before any recommendation, a focused diagnostic identifies the real structural constraint — not the symptom being managed. In both engagements, the surface problem was different from the structural problem. This phase takes 1–3 sessions and produces a written misalignment map.

02

Scoped Intervention

One structural problem, one focused intervention. the first client needed repositioning and market entry strategy. the second client needed architecture de-risking and validation design. Scope discipline prevents the diffusion of effort that dilutes impact in advisory work.

03

Embedded, Not Handed-Off

Recommendations don't end in a document. Both engagements involved working alongside the teams through execution — adjusting in real time as the market, users and organization responded to structural change. The advisory artifact is a record, not the deliverable.

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