Quanthome Data Engine
From scattered documents to one structured, audited view. Quanthome turns the data trapped in your spreadsheets, PDFs, and data rooms into one secure base, in days, not months. Every figure is validated and linked back to its source. Bring one reporting cycle, and we will structure it with you.
Inside the engine
Inside a secured layer, two engines turn your scattered documents into one structured, audited base: every figure traceable to its source.
What runs on the structured base
Structuring and audit build the base; exploration and an AI-ready surface make it ready to use.
Data Quality Engine
Information scattered across spreadsheets, PDFs, and data rooms is structured automatically for agentic use cases, standardized, and entity-matched across your sources.
Data Audit Engine
Testing agents validate every figure and cross-check each other's work, keeping each number traceable to the record, and the document, it came from.
Data exploration
Query your structured data next to Quanthome's market coverage, so internal figures and external benchmarks read against each other in one view.
An AI-ready base
The structured base is built for agentic use and reachable through the platform, API and MCP, so your data and Quanthome's are ready for the workflows that run on top.
Why teams pick Quanthome
Three things set the engine apart for finance and real estate.
Entity matching
We resolve the same asset, fund, or counterparty across documents and registries, so your data joins up instead of fragmenting, the hard part of structuring, solved.
Real estate data
The engine matches your holdings against the full real estate market and 140+ vehicles, the deepest ground-truth available, so structured data lands against real assets.
Model-agnostic
The infrastructure is agnostic from the models: we orchestrate the best model for each task and swap them as they improve, so you are never locked to one vendor.
The jobs this product enables
These are the jobs that depend on your data being structured, reconciled, and audited first.
Portfolio reconciliation
Reconcile internal books against administrator statements, valuations and bank data in one structured base, every variance flagged with its source, so errors surface before the audit and each cycle is a refresh, not a rebuild.
Data room audit
Query a full data room in plain language and hand over reports where every figure cites its source.
What we guarantee for your data
- AnonymizationClient data is anonymized inside the engine, so structuring and analysis never expose identifiable holdings.
- No training on client dataYour data is never used to train models, and serves only your own reports and analysis.
- No distributionClient data is never shared, sold, or distributed to any third party or other client.
- No retentionData is retained only as long as the engagement requires it and is then removed, never kept beyond its purpose.
Questions we hear most
Does the Data Engine see our raw data?
Your data is structured inside the engine and anonymized. It is never used to train models, never distributed, and never retained beyond what the engagement requires.
How is the annual fee set?
The annual fee is scaled to the organization and includes the licenses. We size it in the working session once the scope of the data and the reporting cycle is clear.
What does an engagement include beyond the structured base?
Every deployment includes twelve months of working sessions with your team to ship workflows, embed them, and keep them improving after go-live. The workflows encode your processes and stay yours (you run and adjust them, and keep them after the engagement) while the system learns your processes at scale, so institutional know-how becomes deployable workflows instead of living in a few people's heads.
Can we keep our own report templates?
Yes. You define the templates and the engine populates them from structured data, so the output matches the format your investors and auditors already expect.
Let's discuss your project
Bring one reporting cycle and its current data. We will map how the Data Engine structures it and produces the deliverable from a template you control.
Let's discuss your project