AI strategy
Where AI fits — grounded in your P&L.
AI strategy without the fog.
An honest read on where AI creates value in your business — and where it's a distraction. Roadmap, architecture, build-vs-buy, vendor shortlists, pilot design.
Delivered from Kabul
AI consulting — delivered by senior teams based in Kabul, governed under ISO 12207 and ISO 27001. Twenty years of enterprise delivery in Afghanistan, including the 500,000-employee national-government Odoo HR rollout and Jobs.af. Engagements run from our Kabul office with regional support in Dubai and India.
- 500,000-employee Odoo HR engagement for a national government
- Jobs.af — Afghanistan's largest job-hunting platform — built by NETLINKS
- Clients include Da Afghanistan Bank, Afghanistan Payments System, AKDN, World Bank, UNDP
Why most AI strategies die in the 'somewhere we should pilot' phase.
The average Fortune 1000 AI strategy runs 40 pages, names 20 use cases, ships zero. The strategy isn't wrong — it's not executable. Use cases without architecture, ownership without capacity, budgets without success criteria.
We start the other way — what can we ship in 12 weeks? Then back into architecture and roadmap. We've talked clients out of AI projects as often as into them. That honesty is what you're paying for.
— Engagements
What we advise on.
Roadmap
12-24 month phased plan, quarterly reviews.
Architecture
Data, models, governance, observability.
Build vs. buy
Vendor shortlists, capability matrices, TCO.
Governance
Policy, risk framework, compliance readiness.
Pilot design
Structured pilots with measurable outcomes.
— Honest fit
Our engagement model.
Good fit
- Executive teams wanting an honest, implementation-grounded strategy
- Mid-market to enterprise with serious AI investment appetite ($500K+)
- Organizations evaluating build-vs-buy across multiple use cases
- Companies that have pilot-ed and stalled, wanting a production path
Poor fit
- Companies wanting a 40-page strategy deck to send to the board
- Organizations not ready to actually invest in execution capacity
- Clients who want a Gartner-style market map rather than a plan for their business
- Very early-stage experimentation with budget under $50K
— Questions
AI consulting — FAQ.
How long is a typical engagement?
Strategy and roadmap: 6-10 weeks. Architecture review: 3-4 weeks. Build-vs-buy analysis: 2-4 weeks. Pilot design and delivery: 8-12 weeks. We time-box engagements and define deliverables precisely so the scope doesn't drift.
Do you implement or just advise?
Both. We advise often and implement when the scope fits our squads. If implementation isn't our fit, we help you pick and manage another partner. We don't pretend to have capabilities we don't have.
What's different from McKinsey QuantumBlack or Accenture?
Scale and specificity. Big 4 strategy houses deliver broader market frameworks and multi-year programs with deep executive alignment work. We deliver implementation-grounded, 12-week-shippable plans. Our rates are a fraction of theirs and our recommendations are constrained by what we'd have to deliver — which makes them more executable.
Who does the work?
Engagements are led by a senior partner (hands-on, not just oversight) with one or two specialists (data architect, ML engineer, ethicist/governance specialist depending on scope). No junior-led strategy consulting.
What about regulated industries?
We've done AI strategy for healthcare, financial services, government, and defense clients. Regulatory readiness is a first-class concern — we incorporate GDPR, HIPAA, GLBA, or sector-specific requirements into architecture and governance design from the start, not as compliance retrofits.
Where should AI go first?
1-hour use-case mapping with a senior AI strategist. High-ROI candidates and a 90-day pilot path — written, not theoretical.
Get a use-case map