From map to a sequenced plan.
Workflows, systems, and where time and error actually accrue.
Readiness and each opportunity on value × feasibility × risk.
Expected value and cost for the shortlist, transparently.
A roadmap of experiments, each with a hypothesis and a metric.
Six ways we build the plan.
For leaders who need to know where AI actually moves the needle — and where it does not — before committing budget.
AI readiness assessment
Data, talent, tooling, and process maturity scored against where you are trying to go.
Use-case discovery & prioritization
A portfolio of opportunities ranked by value, feasibility, and risk.
ROI & business-case modeling
Honest expected value for each candidate — including the ones not to fund.
Build-vs-buy analysis
Where to buy a tool, where to build, and where to wait.
Operating model & org design
How AI work gets owned, staffed, and governed inside your walls.
Sequenced roadmap
A phased plan from quick wins to compounding bets.
Value × feasibility — funded honestly.
We plan backward from outcomes.
Most AI strategies start with a technology and hunt for a use case. We do the opposite: we start from the business outcomes you are accountable for, trace them to the capabilities that would move them, and only then decide what to build, buy, or partner for. That single reversal is what keeps a roadmap honest.
Outcome-first, not tech-first
We start from the business result you need and work backward to the AI — never the other way around.
Evidence over enthusiasm
Every use case is scored on real value and real feasibility, so the roadmap funds what actually pays off.
Thin slices, fast proof
We prove value in weeks with a narrow slice before anyone commits to the full build.
Honest build-vs-buy
We recommend buying or partnering when that wins, and building only where it is a durable advantage.
What a roadmap looks like.
A Stryki roadmap sequences work across four quarters: foundations and quick wins land first, the bigger automation bets are staged behind the data and governance they depend on, and operating discipline runs the whole way through. An illustrative shape below.
How the outcomes get delivered.
Every initiative on the roadmap is tied to a chain of measurement — a leading metric we can move in weeks, a business metric it drives, and the financial outcome it lands. We baseline each one before we build, so the value is proven, not asserted.
From assessment to a funded plan.
The services that make up a strategy engagement — take them end to end, or start with the one that unblocks you.
AI opportunity assessment
We map your functions and processes to where AI actually moves a number, and size the prize honestly against effort and risk.
Use-case prioritization & business case
We score candidates on value and feasibility, then build the business case and ROI model that earns the funding.
Data & platform readiness
We assess whether your data, tooling, and cloud can support the use cases, and pinpoint the gaps that would block them.
Target architecture & build-vs-buy
We design the reference architecture and make honest build, buy, or partner calls for each capability.
Operating model & governance design
We define the roles, ways of working, and governance that let AI scale without losing control.
Roadmap & sequencing
We sequence it all into a phased plan — quick wins first, bigger bets staged behind the foundations they need.
Questions teams ask.
Bring us a hypothesis. Leave with a system.
Tell us what's eating your team's time. We'll give you an honest read on whether AI is the right tool — and if it is, a scoped v1 with a timeline and cost.