AI strategy consulting for organizations
A larger organization has more AI ideas than budget to fund them. We start the strategy work with an assessment: a use case portfolio, ranked by payback, with a roadmap attached. The plan tells you, per use case, what fits a custom build and what an off-the-shelf product, and where the data has to be put in order first. Delivered by a Budapest-based team.
The next step is the AI opportunity assessment: from HUF 500,000 + VAT.
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The executive question is the same in most places: which of the many AI ideas pay back, and in what order to build them. The assessment answers it with numbers: cost, benefit, and payback time per use case, in one ranking. If an idea does not pay back, that shows up too — the ranking comes with the reasoning written down.
Across our 46+ completed projects, automated processes reach a 40-45% efficiency gain; the typical ROI timeframe is 6-12 months. At a freight forwarding client, invoice processing went from 3 days to 4 hours; at a manufacturer, defect detection reached 94% accuracy with a model trained on 14,000 labeled images; at an insurance company, 78% of staff used the knowledge base built on 12,000 documents within the first month. Our founder led a multinational corporation's global automation and AI centre of excellence for five years, with a 20+ person international team and $6M+ in annual savings.
Governance is part of the strategy: we run the EU AI Act risk classification at the portfolio stage, so the cost of the obligations shows up in the ranking. A full team carries the work: a project manager, senior developers, and an AI DevOps engineer; we operate enterprise AI platforms with GitOps deployment and blue-green releases, and build RAG and agent systems at production quality. For smaller companies, our AI Consulting for SMEs page describes the same model, sized for 10-50 person teams.
What the strategy work delivers
A use case portfolio ranked by payback
We collect the candidates together with your process owners and estimate cost, benefit, and payback time per use case. The ranking shows where to start — and what to let go.
Custom build or off-the-shelf, per use case
We tell you where custom development pays off, where an off-the-shelf product or subscription does, and where extending your existing systems is enough. The criteria — data protection, integration, operating cost — are written down per use case.
The state of your data, per use case
We check whether the data exists for the use case, in what quality, and with what access. Where it is missing or messy, the plan states the data work as a prerequisite — so the pilot goes to a use case where the data is already there.
Governance and EU AI Act as part of the strategy
We run the risk classification at the portfolio stage, so the cost of the obligations — documentation, human oversight, logging — is visible in the ranking. We have experience implementing high-risk AI systems as well.
How we work
- 1
AI opportunity assessment — from HUF 500,000 + VAT
Interviews with your process owners, a review of your systems and data. The output is a written strategy: a use case portfolio ranked by payback, with custom-or-off-the-shelf recommendations and risk classification. You can use it even if you continue without us.
- 2
Roadmap and pilot selection
The ranking becomes a roadmap: what gets built first, what waits for the data work, and what stays out. For the pilot we pick the use case where the result is measurable, the data exists, and the scope can be bounded.
- 3
Pilot — 2-3 weeks
We test the selected use case in production conditions and measure the results. A small proof of concept is ready in 2-3 weeks; the pilot numbers decide the continuation.
- 4
Implementation and operations — 6-12 weeks
Most projects go from kickoff to production in 6-12 weeks. Source code, models, and data remain yours; monitoring and support are part of how we work.
Why Leventech
Enterprise AI program leadership from the inside
Our founder led a multinational corporation's global automation and AI centre of excellence for five years: a 20+ person international team, $6M+ in annual savings. We bring the same model: measurable goal, pilot, production.
Our team has built production systems since 2013
46+ completed projects, 96% client satisfaction. What we build, we also operate and maintain.
Production-grade platform operations
We operate enterprise AI platforms with GitOps deployment and blue-green releases, and build RAG and agent systems at production quality. The strategy comes from the team that also carries the implementation through.
EU AI Act and GDPR built into development
Risk classification at project start, data protection in the design. We do the technical and organizational preparation; the legal assessment stays with your legal counsel.
Common questions
A use case portfolio ranked by payback, custom-or-off-the-shelf recommendations, a review of the state of your data, risk classification, and a roadmap — in writing. The assessment starts from HUF 500,000 + VAT, and you can work with the output even if you continue without us.
By payback: for each use case we estimate cost, benefit, and payback time, and check whether the process is measurable and the data exists. Across our 46+ completed projects, automated processes reach a 40-45% efficiency gain; the typical ROI timeframe is 6-12 months. If an idea does not pay back, we write that down too.
The plan gives the recommendation per use case, with the reasoning — the factors: data protection, integration, running cost. Price bands for the decision: an AI assistant or integration project is usually €15-40K; a document processing system €30-80K.
The assessment checks, per use case, whether the data exists, in what quality, and with what access. Where it is missing or messy, the plan states the data work as a prerequisite and the use case moves down the ranking. The pilot goes to a use case where the data is already there.
By three criteria: the result is measurable, the data exists, and the scope can be bounded. A small proof of concept is ready in 2-3 weeks and gives you baseline numbers; those decide the continuation.
The EU AI Act classifies AI systems by risk — unacceptable, high, limited, and minimal — and the obligations become applicable in stages between 2025 and 2027. We run the classification at the portfolio stage, and the provider and deployer roles are clarified there too, so the cost of the obligations shows up in the ranking. The details are on our EU AI Act Compliance page; the legal assessment stays with your legal counsel.
After the assessment, a small pilot is ready in 2-3 weeks; most implementation projects go from kickoff to production in 6-12 weeks. The typical ROI timeframe is 6-12 months. Source code, models, and data remain yours.
Still have questions?
Related resources
Start with a conversation
Tell us which AI ideas are on the table and what the goal is — we tell you which ones pay back and where to start.
What would you automate in your business?
Tell us briefly about the task. We will reply by email to arrange an initial conversation.
The next step is the AI opportunity assessment: from HUF 500,000 + VAT.
What happens after you send?
In the first conversation we review the task, your existing systems and the outcome you need. Then we discuss whether a detailed assessment would help. We provide a proposal before any paid work.
Or reach us directly:
[email protected]
Monday-Friday, 9:00-17:00 CET