PROJECTS

Project showcase

A selection of representative engagements and projects from past work. Company names, project names, and identifying details are omitted for confidentiality.

FINTECH · AI PRODUCT & GROWTH

AI-enabled FinTech platform, 0→1→scale

Situation.: A multi-product FinTech portfolio with weak engagement, unclear positioning, and spend that wasn't converting — several products competing for attention without a clear core user.
Intervention.: Defined four core personas and refocused the roadmap and messaging around the highest-value ones. Rebuilt acquisition and activation around those personas, tightened onboarding, and ran a weekly experiment cadence with engineering, data, and design. Owned the product portfolio end-to-end — PRDs, roadmap, and growth — and built and managed the team delivering it. Across the portfolio this included a perpetuals investment platform and an AI-assisted investing experience that profiles a user's risk posture to propose suitable assets — designed to remove complexity for investors in their late 30s–50s who are interested in non-traditional securities but are not crypto-native.
Evidence.: ~2.5× user growth and doubled revenue within a year; engagement up materially.
Capacity: In-house product & growth lead (operating role).
Team: cross-functional team of 8.
Responsibilities.: Owned product and growth for the portfolio: personas, roadmap, PRDs, experiment cadence, onboarding and activation, KPI design, and stakeholder alignment — including building, hiring, and managing the cross-functional team delivering it.

APPLIED AI · PRODUCT STRATEGY

Reframing a stalled AI product, and opening an enterprise path

Situation.: A consumer conversational-AI product built on a strong proprietary language model, but with stalled engagement and weak monetization — strong technology, unclear product-market fit.
Intervention.: Ran funnel analysis across onboarding, repeat use, and channel feedback to find where the product actually resonated. Reframed the consumer experience around a higher-retention use case, then designed the strategy and foundation to extend the same engine into a B2B knowledge/onboarding product (a private retrieval-grounded assistant), including the RAG approach and an evaluation rubric for answer quality, latency, and cost.
Evidence.: On the consumer side, materially improved early-week retention within weeks. The B2B concept advanced from idea to a working enterprise path, substantially reducing time-to-first-answer in onboarding scenarios.
Capacity: SDTR consulting engagement.
Team: worked with the client's product and engineering teams.
Responsibilities.: Led discovery and funnel analysis; defined the retrieval and evaluation approach; wrote the product requirements; set the B2C→B2B direction and the metrics to steer it.

APPLIED AI · PRODUCT STRATEGY + POC

Applied-AI product strategy with a shipped prototype

Situation.: An AI-native product opportunity requiring both a defensible strategy and a working proof — the question wasn't "what's the deck," it was "show the thing working."
Intervention.: Produced an end-to-end product strategy (diagnosis, sequencing, monetization logic, and metrics) and shipped a working prototype demonstrating the core flow — an operator-maintained data layer feeding an AI-agent interaction — deployed and demonstrable, with honest documentation of what was real versus simulated.
Evidence.: A deployed, defensible Stage-0 prototype plus a strategy detailed enough to withstand technical scrutiny.
Capacity: SDTR consulting engagement.
Team: solo, with client stakeholders.
Responsibilities.: Delivered the end-to-end strategy — diagnosis, sequencing, monetization logic, metrics — and built and deployed the working prototype.

APPLIED AI · RAPID PROOF-OF-CONCEPT

Rapid proofs-of-concept for early validation

Situation.: Teams needing evidence before committing serious build — an AI opportunity on the table, stakeholders unaligned, and no working proof to decide with.
Intervention.: A repeated pattern across engagements: align with stakeholders and management on the question that matters, analyze the competitive landscape, then scope and build a working proof against it — conversational agents, retrieval-grounded knowledge assistants, multi-agent automation, AI forecasting. The same discipline is applied outside client work: SDTR regularly builds under competition conditions to pressure-test new frameworks, technologies, and product concepts with external validation — staying at the edge instead of reading about it.
Evidence.: Client PoCs that advanced to pilots and product decisions. Competition builds took first place at the Google Japan / DeepLearning.AI AI Voice Agents Hackathon and won four awards at ETHGlobal Tokyo.
Capacity: SDTR engagements and independent competition builds.
Team: solo or small cross-functional team.
Responsibilities.: Stakeholder alignment, competitive analysis, PoC scoping and build — product definition through working demo.

CONSUMER / DTC · PRODUCT

Product invention for an underserved segment

Situation.: An established but conservative premium-goods category, dominated by heritage players, sold almost entirely offline through intermediaries. Little product innovation at accessible price points, and no direct relationship with a younger, digitally-native buyer.
Intervention.: Identified an underserved segment — high-earning, time-poor, design-driven buyers priced out of true personalization — and built a product line specifically for them: premium, customizable, sold directly online before DTC was a common approach. New products were created analytics-first: ecommerce, website, and advertising data fed directly into what got designed and made. The online channel itself was run as a product — multi-country sales, multi-currency payments, BNPL and crypto payment options — alongside a rapid manufacturing strategy (CAD/CAM, CNC, 3D-printed prototyping) to validate before committing to production.
Evidence.: Profitable in year one; 250% ROI by year two. A signature product sold out at launch and drove unpaid coverage in major international media.
Capacity: Co-founder, product & growth (operating role).
Team: with a co-founder on manufacturing/craft.
Responsibilities.: Led product strategy and the full go-to-market: segment definition, product concept, pricing, the DTC model, payments and channel innovation, and the data-to-product loop.

ENGINEERING · DELIVERY LEADERSHIP

Internal tooling that scaled across a large organization

Situation.: A services organization running 40+ contact centers across Europe, each with its own tools and processes — onboarding a new client or center took two weeks, and inconsistency slowed delivery.
Intervention.: Led a small engineering team to build internal tooling that standardized the work: a live analytics dashboard fed by database replication, a drag-and-drop system for spinning up new phone-handling flows, and a campaign-configuration tool to cut rollout friction. Gathered best practices across centers and embedded them into the tools.
Evidence.: Cut new-client onboarding from ~14 days to ~2; internal quality scores for new integrations rose sharply. The tooling was adopted into regional operating playbooks.
Capacity: Team lead (operating role).
Team: 8 engineers.
Responsibilities.: Led the 8-engineer team; designed the systems; owned delivery, rollout, and training across the centers.