Data Room Audit with Sources Cited
The problem
An audit or due diligence data room arrives as hundreds of PDFs, spreadsheets and scans, and the questions of the work programme are answered by reading them one by one and re-keying the figures that matter. Each number then has to be traced back to the document it came from, the link a team usually loses in the retyping.
What Quanthome does
Quanthome Audit loads the room as it is, answers the work programme in plain language with the source passages cited, and cross-checks every extracted figure against entity-matched market data. Findings export into your report template with the references attached, so review starts from the citation and the next engagement loads a new room into the same workflow.
Question the whole room, cite every answer.
Query the room in plain language
Ask hundreds of PDFs, spreadsheets and scans for rent rolls, valuations or covenants the way you would brief an analyst, and read every answer back with its source passages cited.
Stop re-keying and reconciling by hand
Extracted figures are cross-checked against entity-matched market data and your source documents, so no one re-types numbers or reconciles each disclosure before a finding can stand.
Export cited, reopen on the next room
Findings export into your report template with references attached, so review starts from the citation, and the next engagement loads a new room into the same workflow, a refresh rather than a rebuild.
How audit teams clear a data room with sources cited
Connect or upload the data room as it is: PDFs, spreadsheets and scans. Quanthome Audit ingests the documents and the Data Quality Engine structures and entity-matches their contents against real assets. Ask for rent rolls, valuations, covenants or missing documents in plain language. RAG retrieval reads the room and every answer returns with its source passages cited. Nothing is asserted without a source, so a finding stands up to review the moment it is made.
The Data Audit Engine cross-checks extracted figures against Quanthome's entity-matched market data and flags what does not reconcile. Cross-checks draw on the indexed real-estate market and 140+ vehicles on one structured base, so a figure is read against the asset it describes. A number is verified twice, against its source document and against the market, before it reaches the working papers.
Findings export into your report template with the RAG references attached, so every figure in the working papers links back to its source document. Review and re-performance start from the citation, not a fresh search, so re-tracing a number costs seconds rather than the time it took to find. The next engagement loads a new room into the same workflow, a refresh, not a rebuild.
Built for
The audit, valuation and due diligence teams that have to trace every figure back to the document it came from.
Explore further
Quanthome Platform
The analyst workbench for real estate.
Quanthome Data Engine
From scattered documents to one structured, audited view.
Quanthome AI
Page-on-demand dashboards, generated from a question.
API & MCP
Your tools, our data.
Quanthome Workflows
From structured data to finished deliverables.
What People Ask Before the First Data Room
What is a data room audit?
A data room audit is the review of the documents assembled for an audit or due diligence engagement (rent rolls, valuations, contracts, covenants) to answer the questions of the work programme and trace each figure to its source. Quanthome Audit loads the room as it is, answers those questions in plain language with the source passages cited, and exports the findings with the references attached.
Where do the answers come from?
From the documents in your data room. Retrieval-augmented generation (RAG) finds the relevant passages and the answer cites them, so nothing is asserted without a source. Extracted figures are additionally cross-checked against Quanthome's entity-matched market data, so a number is verified against the document and against the asset it describes.
Are the citations included in the exported report?
Yes. Every figure and finding exports with its reference to the source document, so review and re-performance start from the citation rather than a fresh search. The working papers keep the link between a finding and the document it came from, which is the link teams usually lose in retyping.
Which AI models does Quanthome Audit use?
Quanthome is model-agnostic. Quanthome Audit runs on the models your firm approves, and the grounding, entity matching and source citations work the same whichever model answers. The controls sit in the workflow, retrieval, citation, cross-checks against market data, rather than in any single model.
Is our data room used to train models?
No. Data rooms stay inside the engagement, are processed on Quanthome's infrastructure and are never used for model training. The documents remain confidential to the mandate and the answers they ground stay within it, so a room can be put to work without its contents leaving the engagement.
CHF 5T+ of Real-Estate Value Indexed. One Data Room Loaded. Every Answer Cited to Its Source.
Bring one data room and your audit programme. We will answer its first ten questions with you, sources cited, in a working session.
Book a working session