Make the right AI decisions — before engineering starts
AI Product Strategy gives your team a sequenced roadmap, cost model, and architecture direction — so every engineering decision is made with intent, not guesswork.
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Moving fast on AI, but unclear on what to build first? That's what AI Product Strategy fixes 
Problems AI Product Strategy solves
Your problem
AI initiatives that go nowhere
Features ship in isolation, engineering time gets spent — but there's no coherent plan connecting AI to business outcomes
our solution
Coherent
AI strategy
A structured plan that connects every AI feature
to a business outcome — with clear priorities
and no wasted sprints. 
Your problem
Decisions under pressure
Model choice, data design — made mid-sprint without full information. Some of those decisions will need to be reversed
our solution
Architecture
defined upfront
Every key technical decision documented
before engineering starts — reversibility flagged
where it matter
Your problem
AI costs exceed revenue
No one modelled inference costs, compute spend, or cost-per-user before building. By the time it's visible, it's already a board conversation
our solution
Cost model
before you build
AI economics modelled per feature and per user
— unit economics visible before a single sprint is committed
Your problem
No arguments to show investors
Features shipped. Nothing to show for it. The AI story for the next fundraise is a demo, not a product
our solution
Investor-ready
AI roadmap
A costed, sequenced plan with measurable milestones
— built to hold up under technical due diligence
Your problem
AI initiatives
that go nowhere
Features ship in isolation, engineering time gets spent — but there's no coherent plan connecting AI to business outcomes
Our solution
Coherent
AI strategy
A structured plan that connects every AI feature to a business outcome — with clear priorities and no wasted sprints. 
Your problem
Rushed architecture decisions
Model choice, data design — made mid-sprint without full information. Some of those decisions will need to be reversed
Our solution
Architecture defined upfront
Every key technical decision documented before engineering starts — reversibility flagged where it matter
Your problem
AI costs exceed
revenue
No one modelled inference costs, compute spend, or cost-per-user before building.By the time it's visible, it's already a board conversation
Our solution
Cost model
before you build
AI economics modelled per feature and per user — unit economics visible before a single sprint is committed
Your problem
No arguments
to show investors
Features shipped. Nothing to show for it. The AI story for the next fundraise is a demo, not a product
Our solution
Investor-ready
AI roadmap
A costed, sequenced plan with measurable milestones — built to hold up under technical due diligence
our approach
How AI Product Strategy turns unclear AI ideas into a sequenced build plan
STRATEGIC CLARITY
Know what to build
— and what not to use cases, priorities, and tradeoffs defined by business value before development starts
PRIORITISED ROADMAP
Build the right features first
every AI use case sequenced by value, feasibility, and cost efficiency
COST VISIBILITY
No infrastructure surprises inference
costs, compute, and cost-per-user modelled before engineering begins
ARCHITECTURE FIRST
Decisions made before pressure hits
model choice, data design, and build vs buy are resolved upfront
BUILD VS BUY DECISIONS
Informed decisions
on every component build and buy evaluated per use case — before committing to development
QUALITY STANDARDS
Define success
AI analyzes your business data and live calls to deliver a complete strategy in 7–14 days.
STRATEGIC CLARITY
Know what to build
— and what not to use cases, priorities, and tradeoffs defined by business value before development starts
PRIORITISED ROADMAP
Build the right features first
every AI use case sequenced by value, feasibility, and cost efficiency
COST VISIBILITY
No infrastructure surprises inference
costs, compute, and cost-per-user modelled before engineering begins
ARCHITECTURE FIRST
Decisions made before pressure hits
model choice, data design, and build vs buy are resolved upfront
BUILD VS BUY DECISIONS
Informed decisions
on every component build and buy evaluated per use case — before committing to development
QUALITY STANDARDS
Define success
before shipping output quality standards and evaluation criteria set for each AI feature
AI Product Strategy
Let's map your AI product challenges in a 30-min call
Book an intro call
what you get
A defined architecture, roadmap, and cost model for your AI-powered solution
How it works. From first call to build-ready strategy
[ 1 ]
DISCOVERY & RESEARCH
A scoping call to align on your product, goals, and AI state
[ 2 ]
USE CASE PRIORITISATION
Every AI use case is scored by business impact, feasibility, and cost
[ 3 ]
COST & ARCHITECTURE
Model choice, build vs. buy, and infrastructure costs documented per feature
[ 4 ]
STRATEGY DOCUMENT
Prioritised roadmap, cost model, risk assessment, and 90-day execution plan
[ 5 ]
STRATEGY PRESENTATION
Findings and execution plan presented to CEO and CTO - ready to build from
deliverables
What's included in your AI Product Strategy
At the end of 6 weeks, you will receive a complete strategy document covering:
Prioritised AI feature roadmap
3 to 12 month horizon
Detailed use cases
with estimated impact, complexity, and build assumptions
Technical architecture
and system design recommendations
AI cost model
cost per user, inference costs, infrastructure spend
Data requirements
and data strategy
Build vs buy
and partner recommendations per use case
Competitive analysis
AI capability gaps vs. direct competitors
Risk and compliance assessment
EU AI Act, data residency, AI governance
Resource estimates
team, timeline, and budget for implementation
‍
AI Product Strategy in practice. Real outcomes from real engagements
AI
CMS
DATA
AWS
BI
GCP
ML
AI-powered Disinformation Monitoring Platform for Central Europe
View case study
AI
CRM
GenAi
Rag
Data
Azure
AI Agents
AI-powered CRM for private equity investors
View case study
AI
Azure
Agents
GenAI
RAG
AI Assistant for Private Equity Investment Platform
View case study
AI
AWS
CRM
Data
BI
Ad Analytics Platform for High-Volume Campaign Management
View case study
View more cases
testimonals
What business say about AI Product Strategy
No European newsroom can face cognitive warfare alone. Katalin brings journalists together around shared AI power and cross-border intelligence.
It turns collaboration into a defense system that learns, adapts, and keeps them one step ahead. With Katalin we tried to shape the first barrier in collective resilience of CEE journalism to the rising tide of cognitive warfare.
Maksym Eristavi
Product Lead, Free Press for Eastern Europe
The biggest pain for us was reporting. We used to spend hours just pulling data into spreadsheets, and now everything is there instantly.
There are no more errors from calculations, no more manual work we had to double-check all the time. What used to take days at the end of the month now takes just minutes.Overall, it gave us way more control and speed in how we run large-scale advertising campaigns”
Yulia
Marketing Manager
No European newsroom can face cognitive warfare alone. Katalin brings journalists together around shared AI power and cross-border intelligence.
It turns collaboration into a defense system that learns, adapts, and keeps them one step ahead. With Katalin we tried to shape the first barrier in collective resilience of CEE journalism to the rising tide of cognitive warfare
Maksym Eristavi
Product Lead, Free Press for Eastern Europe
The biggest pain for us was reporting. We used to spend hours just pulling data into spreadsheets, and now everything is there instantly.
There are no more errors from calculations, no more manual work we had to double-check all the time. What used to take days at the end of the month now takes just minutes.
Overall, it gave us way more control and speed in how we run large-scale advertising campaigns
Yulia
Marketing Manager
why now

Waiting doesn't bring clarity
— it adds cost

Engineering time spent building the wrong features
— a runway that can't be recovered
Engineering time spent building the wrong features
— a runway that can't be recovered
Engineering time spent building the wrong features
— a runway that can't be recovered
Engineering time spent building the wrong features
— a runway that can't be recovered
The cost of starting is fixed and known.
The cost of waiting compounds.
Get started
Still unsure what to build first? Let's figure it out together!
Book an intro call
FAQ
Common questions before getting started
We need to start building — not spend time on strategy. Is skipping the strategy saving time?

Building without a strategy is the most expensive option. The cost of rebuilding the wrong AI-powered software, reversing an architecture decision, or explaining poor AI metrics to investors far exceeds a fixed-price strategy engagement. You're not delaying the build — you're making sure the first sprint goes in the right direction

You're not delaying the build — you're making sure the first sprint goes in the right direction

We can figure out the AI strategy ourselves. Can your team define the right priorities before the next sprint starts?

Most teams can produce a list of AI ideas. The hard part is deciding which ones are worth building, in what order, at what architecture cost, and with what success criteria — before committing months of engineering time.

That's exactly where internal efforts stall

We outsourced AI development to a dev shop. Why do we still need a strategy?

If they don't provide strategic direction — what to build, why, and at what cost — you have execution capacity pointed at an unclear target. A dev shop takes a feature list and builds it.

AI Product Strategy defines the feature list first

AI moves too fast to plan. Is moving fast without a plan really faster?

The goal isn't to predict every model release. It's to make the right decisions about what to build now, with enough architecture flexibility to adapt as the technology evolves.

That's what modular architecture and phased roadmaps are built for

We're hiring a Head of AI to own our AI strategy. Why would we need this engagement?

Senior AI talent is scarce, expensive, and takes 2–3 months to onboard before meaningful output. AI Product Strategy delivers a clear roadmap in 6 weeks

— and the team that built the strategy can execute it immediately after

We already started building. Is it too late for create AI Product Strategy?

It's rarely too late. A strategy engagement can validate what's been built, surface the decisions that still need to be made, and create a clear path from the current state to production

What exactly is included in AI Product Strategy?

You receive a prioritised AI feature roadmap, technical architecture recommendations, AI cost model, build vs. buy analysis, competitive analysis, compliance assessment, and a 90-day execution plan

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