Roadmap workshops, AI readiness audits, build-vs-buy decisions, and architecture reviews. We help boards and CXOs decide what to build, what to defer, and what to never touch - grounded in forty production deployments, not slides borrowed from a research firm.
What this is
Most AI strategy decks are written by people who haven't shipped a production system. Ours are written by architects who have shipped forty. AiSPRY's strategy practice has been advising CXOs and boards since 2018 - built on the painful lessons of what actually breaks between pilot and production.
Our outputs are decisions made - what to build, what to buy, what to defer, what to kill - not 80-slide decks for the board to admire. Every engagement ends with a written, dated, signed-off roadmap.
Recommendations are stress-tested against real architecture, real data shape, and real organisational reality. Every "we should build X" comes with a high-level technical sketch and a deployment estimate.
If a vendor product solves your problem better than a custom build, we'll say so - including when that means we lose the implementation work. We've recommended off-the-shelf tools when they were the right answer.
We can implement what we recommend, but we don't have to. Engagements are designed so the recommendation is independent of who builds it. The roadmap is yours; the engagement isn't a sales funnel.
How we do it
Each engagement is scoped tightly with clear deliverables and a fixed timeframe. We're allergic to open-ended consulting; every engagement has a stop date.
4-week sprint that produces a prioritised, sequenced AI roadmap for the next 12-24 months. Stakeholder interviews, use-case prioritisation, capability mapping, and a written plan with budget estimates.
8-week deep audit of data foundations, organisational capability, technical infrastructure, and current AI/ML investments. Surfaces where you're production-ready and where you're not.
2-4 week focused engagement on a specific decision: build internally, buy a vendor product, or partner. Vendor diligence, total-cost-of-ownership modelling, and architectural fit assessment.
3-week technical review of an existing or planned AI/ML system. Identifies architectural risks, missing components, scalability gaps, and operational debt.
2-3 week sprint to prioritise a backlog of AI/ML opportunities. Value-vs-effort scoring, capability dependencies, and a phased delivery plan.
Ongoing advisory engagement - typically a half-day per month with a senior architect. Used by clients with internal AI teams who want external sense-checking.
Use cases
A representative selection - strategy engagements vary widely. Below are the patterns we see most often.
Multi-year AI investment roadmap with use-case prioritisation, capability gaps, and phased budget estimates. Used by boards making capital allocation decisions.
Audit of existing AI capability, gaps, and recommended hiring/build/partner mix to build an internal AI function. Used by growing companies hitting AI strategy questions.
Independent diligence on AI/ML vendors before purchase, or build-vs-buy assessment for specific capability needs. TCO models, architectural fit, vendor risk.
Technical review of existing AI/ML systems - production architecture, operational debt, scalability, drift handling, observability. Findings + recommended remediation plan.
Sector-specific use-case discovery and prioritisation - manufacturing, energy, healthcare, financial services. Grounded in production references from those sectors.
Setting up internal AI governance - risk frameworks, model approval processes, monitoring requirements - for organisations rolling out AI at scale.
Tech stack
Selected work
12-month AI roadmap covering predictive maintenance, demand forecasting, and computer vision use cases - sequenced, budgeted, with capability gap analysis and a phased hiring plan.
Independent assessment of three GenAI platform vendors against in-house build option. TCO modelling, vendor diligence, architectural fit. Recommendation: hybrid - buy retrieval, build agents.
3-week architecture review of existing ML platform before national rollout. Identified drift monitoring gaps, observability holes, and a feature-store readiness gap. Remediation plan delivered.
Frequently asked
Quick answers to what teams ask before bringing us in. Don't see your question? Talk to us directly.
We're architects who have shipped forty production systems. Our recommendations are stress-tested against real implementation experience - what actually breaks between pilot and production, what data foundations actually need, what vendor lock-in actually feels like in year three. Big firms send partners with deep slides and junior teams with no production scars; we send architects.
Roadmap workshops are 4 weeks. Readiness audits are 8 weeks. Build-vs-buy advisory is 2-4 weeks. Architecture reviews are 3 weeks. Use-case prioritisation is 2-3 weeks. Quarterly advisory is ongoing - typically half a day per month. We're allergic to open-ended consulting; every engagement has a stop date.
No. If a vendor product solves your problem better than a custom build, we'll say so - including when that means we lose the implementation work. We've recommended off-the-shelf tools when they were the right answer. The engagement is structured so the recommendation is independent of who implements it.
Week 1: stakeholder interviews and use-case discovery. Week 2: capability gap analysis and architectural sketches per priority use case. Week 3: prioritisation workshops with the leadership team - value scoring, effort scoring, dependency mapping. Week 4: written roadmap with budget estimates, phased delivery plan, and a board-ready summary. The output is a signed-off, dated document.
Yes. A meaningful share of our strategy work ends with us recommending we don't build it - either because a vendor is a better fit, or because the client's internal team is well-positioned to execute. We charge fixed-price for strategy engagements precisely so this is a genuine choice, not a sales funnel.
We ship production AI every quarter. Strategy advisors who don't ship lose touch fast - the gap between what's possible in research and what's deployable in production is our daily reality. Every architect on a strategy engagement is also on or fresh off an implementation engagement.
30-minute call with a senior architect. We'll scope the right engagement type, give you a fixed-price proposal, and tell you honestly if we're the wrong fit for the question.