Engineering · Data · AI for Private Markets

Your data and engineering team for private markets.

Qstrat combines deep data science and quantitative expertise with production engineering. We build the pipelines, computational engines and AI systems that GPs, LPs and analytics providers run on. We build the technology. You own the insight.

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Built for Fund managers (GPs) Asset owners (LPs) Fund-of-funds Consultants & placement agents Analytics providers

Services

Three pillars of technology for private markets.

We engineer the systems behind private markets analytics. They are tested, documented and built to run every quarter without manual rework.

01

Analytics Engineering

The computational engines behind private markets analytics.

  • Calculation libraries for performance metrics, at scale and fully tested
  • Configurable benchmarking and peer-comparison engines
  • Custom analytics applications and dashboards
  • APIs and microservices for internal and client tools
  • Migration of legacy Excel and Access models to production code
02

AI & Machine Learning Systems

Applied AI infrastructure designed for private markets data.

  • AutoML pipelines for training, validation and deployment
  • LLM and RAG systems over documents and deal data
  • Document processing for GP reports, capital account statements and data rooms
  • AI agents that automate research and data collection
  • News and unstructured-data monitoring with NLP and sentiment models
03

Data Platforms & Automation

Cloud data infrastructure that replaces manual spreadsheet work.

  • ETL pipelines for GP, LP and third-party data vendors
  • Data warehouses and SQL data models on Azure and other clouds
  • Automated Excel, PowerPoint and PDF reporting
  • Data quality, validation and reconciliation frameworks
  • DevOps, CI/CD and managed hosting for analytics apps

Expertise

Data scientists who engineer. Engineers who understand the numbers.

Our team is rooted in quantitative finance and data science. We understand the mathematics behind private markets performance as well as the code that computes it, so the systems we build are both correct and robust.

∫ IRR

Private markets quant

Cash-flow and NAV mathematics, public market equivalents, return attribution and peer-relative statistics.

ŷ = f(x)

Machine learning

AutoML, ensembles and rigorous out-of-sample validation on sparse, noisy tabular data.

σ · N

Simulation & statistics

Monte Carlo portfolio simulation, cash-flow forecasting, persistence studies and hypothesis testing.

LLM · NLP

Language AI

Retrieval-augmented generation, entity matching, document extraction and financial sentiment models.

How we work

An engineering partner, not another analytics vendor.

You keep the methodology

We implement your models and conventions in code, and the analytical judgement stays with you. Where it helps, we act as thought partners in refining and improving them.

Validated to the cell

Every pipeline is reconciled against your existing reviewed output before it goes live.

Confidential by design

Client data stays in client-approved environments, with strict separation between engagements.

Case studies

Selected work.

AI & Machine Learning Systems

Filling missing data at scale with an agentic RAG architecture

A model cascade routed by difficulty for ~35,000 records: deterministic scoring first, reasoning models only for conflicts, every output grounded in a source.

>90% lower inference cost77% exact match, held-out set≈ €0.015 per record Read the case study →

Clients

Built for private markets players.

Fund managers (GPs)

Automated data rooms, reporting and fundraising support systems that turn quarterly data work into a repeatable process.

Asset owners (LPs)

Data platforms, monitoring and AI tooling for portfolio construction, manager selection and investment decisions.

Analytics providers

Product engineering and data science for firms such as Gottschalg Analytics, our longest-standing client.

Get in touch

Talk to the team engineering analytics for leading GPs and LPs.

Tell us about your data, your reporting cycle or the system you want built. We'll reply within two working days.