SERVICES

What we do.

Six ways SDTR helps teams turn AI capability into products that ship and grow.

AI Readiness & Opportunity Assessment

Best suited to.: Teams that know AI matters but don't yet know where it creates value for them — the "we should be doing something with AI, but where do we start" situation.
Typical deliverable.: A scoped assessment: where AI realistically creates value in your business, what's technically feasible, and a sequenced plan — with the low-value and high-risk options ruled out.
Result it enables.: A clear, prioritized starting point instead of a stalled proof-of-concept — and a defensible plan you can act on.

Best suited to.: Teams about to commit heavy build to an idea that hasn't been tested — where the risk is spending months before learning whether it works.
Typical deliverable.: Customer discovery, prototypes, and structured tests that produce evidence — proof (or disproof) before the expensive build.
Result it enables.: A go/no-go decision grounded in real signal, not opinion — and saved build time on the ideas that don't hold up.

Best suited to.: Teams turning AI capability into a real product — agents, assistants, retrieval-grounded features — that has to survive contact with actual users, not just demo well.
Typical deliverable.: A working AI feature or product with an evaluation approach (task success, quality, latency, cost), sensible guardrails, and a clear line between what the model decides and what deterministic logic decides.
Result it enables.: An AI product you can ship with confidence — measured, guarded, and honest about what it does and doesn't do.

Best suited to.: Products that need to find, activate, and retain users — including launches that cross borders (Japan ↔ global) where the model has to fit local reality.
Typical deliverable.: Activation, retention, and monetization work — experiments, funnel improvements, pricing, and localized go-to-market — driven by real data.
Result it enables.: A product that pays off, not just launches — with the growth loops and pricing to sustain it.

Best suited to.: Teams with more ideas than sequencing — where the question is "what do we build, in what order, and how do we know it's working."
Typical deliverable.: A prioritized roadmap tied to clear goals and KPIs, with the delivery cadence and review rhythm to keep it moving.
Result it enables.: A team that can say what it's building this quarter and why — and can tell whether it's working.

Best suited to.: Platforms and tools that need developers to actually adopt them — where interest exists but hasn't turned into usage.
Typical deliverable.: Developer hackathons, onboarding programs, technical talks, and content designed to move people from curiosity to building.
Result it enables.: Developer interest converted into real adoption and a community that grows through substance.

What clients provide.: Access to the relevant people and context (product, engineering, data, business as needed), and a clear decision-maker on their side. The more direct the access, the faster the work.
Cadence.: A regular working rhythm with weekly evidence — what was tried, what was learned, what's next — so progress is visible, not a black box until the end.
Ownership and handover.: Deliverables and handover materials are documented as set out in the engagement agreement, with the aim of a practical handover and no unnecessary dependency on SDTR.
Stop, extend, or transfer.: An initial project ends with an explicit decision: stop (you have what you needed), extend (deepen the engagement), or transfer (SDTR built it, your team runs it) — practical transfer without unnecessary lock-in.

Defined scope, a specific deliverable — typically 2–6 weeks, depending on scope, access, and client dependencies. The normal way to start.

Ongoing part-time product or AI leadership working alongside your team — cadence, roadmap, and delivery.

For teams that need more, scoped case by case.

SDTR takes on a small number of engagements at a time.

A 30-minute fit conversation.
A written scope: outcomes, deliverables, roles, success measures.
A first project — typically 2–6 weeks depending on scope — with weekly evidence, a decision memo, and a practical handover.

Start in weeks — without waiting for a full-time senior hire, or committing to a permanent role before the problem is understood.