AI Advisory Services

Before you start building, make sure the AI idea is worth the investment and has a realistic path to production.
Trusted by
Netherlands
E-commerce
80,000+

products across 8 markets.

Estonia
Fintech
€4.8M

in loan deals

Sweden
Digital media
Leader

in the local market.

USA
Legal
160x

faster document processing

Germany
Enterprise
200+

EU policies organised

UK
Fintech
500,000+

downloads on Google Play

UK
Green Mobility
50%

revenue growth within a year

Latvia
Fintech
€68M

financed in invoices

WHO WE ARE

AI advisory company for enterprise-scale decisions

Our AI advisory for businesses focuses on one of the hardest parts of AI adoption: deciding what is worth building and whether the organization is ready for it. We work through those decisions with you before development starts, so you know where to invest and what it will take to move forward.

Readiness and maturity assessment

See whether your data, systems, and team are ready for the AI project you have in mind — and what needs attention before it makes sense to move forward.

Governance and regulatory scope

Understand how the EU AI Act applies to your systems and what needs to be addressed before they go into production.

Roadmap

Turn the decisions made during advisory into a plan your team can work from, with a clear order of priorities and ownership.

Vendor and tool selection

Decide whether to build, buy, or extend what you already use. If an existing product is the better fit, we'll say so.

About

What is AI aadvisory?

AI advisory and consulting services help organizations assess their data and IT infrastructure, select and prioritize use cases, estimate total cost of ownership, and evaluate regulatory requirements.

SEE HOW WE WORK
Watch how our agentic system turns a week of manual work into 5 minutes

Accelerate your operational velocity

Get an engineering assessment to identify where intelligent agentic layers can eliminate processing delays in your infrastructure.

Initiate technical review

Adoption is not the problem

AI is already a given. Now it comes down to choosing the right use cases

88%

of organizations use AI in at least one business function

7%

have fully scaled AI across the enterprise

39%

report enterprise-level EBIT impact from AI

63%

of organizations either don't have or aren't sure they have the data managementpractices needed for AI

McKinsey & Company, Gartner, and Deloitte. Data from 2025 reports and surveys.

When does your business need AI advisory?

You probably don't need another lecture on why AI is important. Business AI strategyadvisory is useful when the real question is what to prioritize, what is feasible, and whatshould happen next. If any of the points below sound familiar, an advisory engagementcan help you make that decision.

You have several AI ideas, but no clear priorities

Identify which use cases justify investment and which should be deprioritized.

You want to adopt AI, but lack a clear starting point

Assess your data, infrastructure, and internal capabilities before choosing a technical approach.

Your AI pilot is stuck before reaching production

Identify the blockers preventing deployment, whether they relate to data pipelines, integration,costs, or governance.

You need to justify an AI investment

Get an objective evaluation of feasibility, total cost of ownership, expected ROI, and resourcerequirements.

You are deciding between building and buying

Get an objective assessment of feasibility, total cost of ownership and resource requirements.

You need a practical implementation roadmap

Establish a structured execution plan that defines project sequence, required resources, andkey milestones.
Services

Our AI advisory services

Most AI transformation advisory engagements combine several of these services. What goesinto the work depends on what you already know and where the open questions still are.

AI readiness assessment

We check whether your current data, systems, and team can support the AI solution you have in mind. For AI analytics advisory projects, this also means looking closely at whether the available data is complete, accessible, and suitable for the decisions the system needs to support.

Use case selection and prioritization

Our AI strategy advisory work starts with a question: which ideas actually deserve investment? We review the options on the table and weigh them against the data available, expected value, and the work involved.

Cost of ownership modeling

The cost of an AI system does not stop once it is built. We account for the expenses that come later, such as model usage, infrastructure, maintenance, monitoring, and human review. This gives you a more realistic estimate of what the solution will cost over time.

AI governance and EU AI Act scoping

We look at how the EU AI Act applies to the system you are planning and flag the requirements that may affect its design or rollout. Certain uses, including recruitment, individual credit scoring, and risk assessment in life or health insurance, may fall under the Act's high-risk rules.

Build, buy, or extend

Sometimes custom development is the right answer. Sometimes an existing product already solves most of the problem. In generative AI advisory, this decision may also involve choosing between an existing model or platform and building additional functionality around it.

Implementation roadmap

Once the main decisions are made, we put them into a workable sequence. The roadmap shows what comes first, what depends on what, and what your team will need to move the work forward.

Have an AI initiative that still hasn't reached production?

We'll identify what is blocking it, what it will take to move forward, and whether further investment still makes sense.

Solutions

Regulations and standards we work with

EU AI Act

We identify the requirements that apply to your system, including high-risk and transparency obligations.

GDPR

We assess how personal data can be used and whether automated decision-making rules apply.

DORA

For EU financial companies, we review ICT risk and third-party requirements relevant to the AI solution.

NIST AI RMF

A voluntary framework we use to structure AI risk management and governance.

ISO/IEC 42001

A management standard for organizations that need a formal approach to AI governance.

What you get

A clear view of the data available for each shortlisted use case
Each use case compared with how the work is done today, so there is a baseline forjudging whether AI is actually an improvement
An estimate of what each solution will cost to run at your expected volume
Your AI systems classified against the EU AI Act, with the requirements that apply andany gaps that need to be addressed
A build sequence showing what should come first, where the dependencies are, and theestimated cost of each stage
The use cases we recommend dropping, and why

How an advisory engagement works

Two conversations, a data check, a cost-and-regulation pass, and a roadmap. Here's what happens at each stage of an advisory engagement:

Interviews

01

Data

02

Cost and regulation

03

Roadmap

04
FEATURED CASES
USA
Law practice
Liner Legal

160x faster document processing for a law firm

Achievements
Speeds up medical record processing 160x (from a week to 5–15 minutes)
Replaces 4 days of manual CRM reconciliation with full automation
Auto-surfaces referral opportunities as a new revenue stream
USA
Fintech

Trading platform with agentic AI for 100k+ investors

Achievements
Speeds up market data processing by 40%
Delivers 90% accuracy in predictive trading analysis
Cuts institutional operational costs by 35%
Sweden
Investment

AI agent system for a multi-billion-euro PE fund

Achievements
Cuts deal sourcing time by 80%
Analyzes 5,000+ investment opportunities in hours
Generates pitch decks in minutes
What our clients say

“They're incredibly detail-oriented, proactive in suggesting improvements, and consistently bring new ideas to improve our systems."

Nerina Valladares
Director of Adv., Liner Legal
By the numbers
168 hours to 5 minutes

Our biggest operational cycle compression in unstructured data processing

27

Autonomous AI agents running live in client environments

93%

of clients return for the next project

15+

Countries running systems built by our team

HOW WE WORK

Engagement and pricing

Our AI advisory consulting services are scoped around the decisions you need to make. A single use case may only need a focused assessment, while an enterprise AI program can involve several teams and systems. We agree on the scope before the work starts, so you know what is included and what it will cost.

Fixed-scope assessment

One defined question or use case, with a set scope and timeline. Suitable for feasibility checks, build-vs-buy decisions, pilot reviews, or readiness assessments. Best when the problem is already clear.

Multi-use-case advisory

We review several AI opportunities together, compare them, and decide which ones deserve investment. The engagement ends with priorities, cost estimates, and a roadmap. Best when you know where AI could help, but not what to do first.

Ongoing advisory

Senior AI and engineering support as your AI program develops. We can review new use cases, vendor choices, technical decisions, or changes to the roadmap as they come up. Best when AI decisions continue beyond a single project.

What drives the cost

Number of use cases
A focused review of one use case takes less work than comparing several initiatives across the business.
Data and system complexity
Data and system complexity. The more sources, integrations, and legacy systems involved, the more work is needed to understand what is feasible.
Depth of the assessment
Depth of the assessment. A high-level feasibility check and a detailed TCO, architecture, and implementation plan require different levels of analysis.
Regulatory scope
Regulatory scope. Projects affected by the EU AI Act, GDPR, DORA require additional review.

Frequently Asked Questions