Logikon Solutions
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About
Logikon Solutions is a two-person data and AI company based in Rotterdam, the Netherlands. We engineer intelligent processes from your data: the pricing, forecasting, planning and scheduling decisions a business still runs on instinct, rebuilt to run on evidence using operations research and machine learning. Our work covers demand forecasting and dynamic pricing, inventory and resource optimisation, geospatial models on satellite and location data, recommendation and propensity models, and LLM agent systems with retrieval, tool calling and evaluation before they go live.
Every project follows our five-step LOGIK process, from locating the decision to handing over dashboards and automated recommendations your team acts on. Founded by Panos and Antonis Mavritsakis, with backgrounds at TU Delft, Arup and Deltares. We start every engagement with a short fixed-scope Diagnostic and quote each project fixed after a scoping call.
Our Take
One of the nine published projects is client work: a demand-forecasting and dynamic-pricing system for a fleet of high-value rental assets, built alongside the client's own teams and validated against their historical static pricing—the client is not named, and the write-up reports no revenue or utilization figures.
The other eight are self-directed: the property-valuation pipeline and the portfolio-rebalancing bot are public repositories on the firm's GitHub, the poker LLM work is presented as an exploration, and the wind-forecasting study was presented at EGU 2020—research and portfolio output rather than delivered systems.
Both founders are named, hold TU Delft master's degrees and list 13 years of combined industry experience, and the Dutch entity is registered at a Rotterdam address (KvK 97755672); the firm itself dates to 2025 and is two people.
Best for a scoped forecasting, pricing or scheduling problem where operations-research method applied to your own data matters more than a reference list.
Key strengths
- Projects are quoted fixed after a scoping call, with a short fixed-scope Diagnostic first, so the €65–100/h listed rate is a reference point rather than the billing model
- Two of the nine projects ship as public GitHub repositories, so the code and its structure can be read before any engagement is signed
- Write-ups name the stack and the evaluation method: GeoPandas, XGBoost and scikit-learn on the valuation pipeline, with MAE, RMSE, MAPE and R² reported
Good to know
- Ask for a speakable reference behind the rental pricing engagement—it is the only client project published, and the client is not named
- Confirm capacity before scoping a multi-month build: the firm is two people, founded in 2025, and both founders are listed as leads rather than a delivery bench
- The FinTech and SaaS listings rest on self-directed crypto and sentiment work, not client delivery—ask for delivery evidence in your own vertical
Reviewed by Gabor Kiss
Founder & Curator, AIAgencies.eu · 20 Sept 2026
Based on the agency's publicly available portfolio. Our assessment is independent—agencies cannot pay to change it.
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