Data Extraction
QFT turns unstructured private market documents, such as GP reports, track records, and data rooms, into structured, queryable data. Schema-enforced, human-verified, and ready for analytics.
Inputs
What we extract from
GP quarterly reports, capital account statements, track record files, portfolio company financials, transaction data, valuation schedules, and data room contents. PDF, XLSX, CSV, and image-based documents are all supported.
Process
How extraction works
Documents are parsed, mapped to the QFT schema, and normalized. The system flags missing fields, inconsistencies, and formatting anomalies. A human reviewer verifies every extracted dataset before any calculation runs on it.
Output
Structured, analytics-ready data
Deal-level cash flows, valuation histories, performance metrics, exposures, and fund terms, all in a consistent schema. Ready for fund manager rating, valuation, and portfolio planning, without analyst cleanup.
What used to take an analyst a full day per fund takes minutes. Quality is higher because the schema is enforced, not improvised per analyst.
What data extraction is not
Extraction is not analysis. The extracted dataset is the input to the QFT methodology, not the output. Analytical judgements such as rating, valuation, and scenario modelling are documented separately under the methodology.
Extraction is also not a replacement for the data governance policies you already have. All extractions run on your data only. Nothing is shared across clients or used for model training. Read more about Data & Security.