Our Story
Our Philosophy
Northhaven Analytics was founded by Oleg Fyłypczuk and Gabriel Wiśniewski with one clear objective: to redefine how financial institutions access, test, and validate data in an era dominated by regulatory constraints and privacy rules. What started as a research-driven experiment evolved into a specialised data company when we proved that synthetic financial environments can accurately replicate real-world behaviour — without using a single piece of sensitive information.
We do not generate random numbers.
We engineer financial reality — structured, correlation-aware, and safe to use across the highest levels of global finance.
Founders
Oleg Fyłypczuk — Financial Systems & Quantitative Logic
Oleg brings the financial and analytical perspective behind Northhaven. His background spans credit modelling, risk analysis, market simulation, client behaviour prediction, and the architecture of data environments used by quantitative teams.
His work focuses on:
- designing financial behaviour models
- structuring multi-variable dependencies
- translating business logic into generative rules
- ensuring datasets reflect real-world market dynamics
- developing synthetic datasets for banks, hedge funds, private equity and fintechs
Oleg ensures that every dataset produced by Northhaven behaves like a real financial system — with realistic variance, imperfections, correlations and lifecycle logic.
Gabriel Wiśniewski — Data Engineering & Algorithmic Architecture
Gabriel is responsible for the technical foundation of Northhaven. His expertise includes building synthetic data engines, backend architectures, dependency models, validation frameworks and scalable dataset pipelines.
He specialises in:
- synthetic data generation engines
- backend and algorithmic architecture
- business-logic implementation
- advanced data engineering for enterprise systems
- QA, validation and reproducibility standards
Gabriel ensures that the data generated by Northhaven is structurally sound, statistically consistent and engineered to meet enterprise-level reliability. His work guarantees that every dataset behaves according to real financial logic while remaining fully reproducible, secure and aligned with the institution’s internal requirements.
Our Mission
To provide financial institutions, quantitative teams and AI developers with high-fidelity synthetic datasets that unlock innovation without compromising privacy, compliance or operational security.
Our Vision
To become the European reference point for synthetic financial data — the partner that top-tier banks, hedge funds, private equity firms and quant teams rely on when they need truth, accuracy and compliance in one unified dataset.
At Northhaven Analytics
We don’t create artificial numbers for the sake of data.
We build structured intelligence — financial environments that behave like real markets, evolve like real clients, and support the most demanding analytical workloads.
This is synthetic data engineered for institutions where precision is not optional — it is the standard.