README.md

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title: README
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# CMD+RVL — Structured finance data intelligence

We turn primary sources — SEC filings and the disclosures behind structured
finance deals — into machine-readable data with the provenance kept intact, so
every number can be traced back to where it came from.

The datasets on this page are **open samplers** of that work. They're built to be
downloaded, modeled, and pulled apart. The full, continuously-updated data that
backs them is available on the
[Snowflake](https://app.snowflake.com/marketplace/providers/GZT0ZYQ5618/CMD%2BRVL%20%28Command%20Reveal%29)
and [Databricks](https://marketplace.databricks.com/?provider=CMD%2BRVL&sortBy=date)
marketplaces — these Hugging Face releases are the taste, not the whole table.

## Explore the data live → [dealcharts.org](https://dealcharts.org)

DealCharts is our public window into structured finance: thousands of CMBS deals,
mapped funds, and BDCs, each backed by the SEC filings it came from. **Ask Cairn**
anything about a deal, fund, or entity and get an answer with its sources. Start
there — it's the fastest way to see what this data can do.

## On Hugging Face

**Available now — CMBS special-servicing early warning.** A leakage-safe
population framed around "which CMBS assets are at elevated risk of transferring
to special servicing within the next 12 months," using only point-in-time
information from SEC filings, in three shapes:

- [`cmbs-special-servicing-transfer`](https://huggingface.co/datasets/commandreveal/cmbs-special-servicing-transfer)
  — flat supervised table for tabular classification, AutoML, XGBoost, and
  tabular foundation models like [TabPFN](https://github.com/PriorLabs/TabPFN)
  and [TabFM](https://github.com/google-research/tabfm).
- [`cmbs-special-servicing-sequences`](https://huggingface.co/datasets/commandreveal/cmbs-special-servicing-sequences)
  — the same population as ordered per-asset sequences, for sequence and
  time-series models.
- [`cmbs-special-servicing-timeline`](https://huggingface.co/datasets/commandreveal/cmbs-special-servicing-timeline)
  — a text companion with a natural-language timeline per observation, for LLM
  prompting, NLP, and text classification.

**What's next.** This is one use case in one asset class. More CMBS use cases,
Auto ABS, CLO, and other structured finance datasets are on the way.

## How to use these

Treat them as starting points, not answers. CMBS is hard, and these tables are
unlikely to be predictive on their own — even cleaned up. They're more
interesting as the *shape* of a problem: a defined population, an honest temporal
split, and traceable provenance to build on. Stitch your own signals onto the
spine — rates, spreads, macro, property-level data, your own features — and see
what actually moves the label.

The point of the provenance is that you never have to take a number on faith:
every observation carries the SEC filing and reporting period it came from, so
you can trace and check any value yourself. We're not claiming the labels are
clean or the feature set complete — we're claiming they're auditable. That's the
same discipline we bring to client work: finished results with proof that survive
without us.

## Terms

License: CC-BY-NC-4.0 — open for non-commercial use. For commercial use, get the
full data on
[Snowflake](https://app.snowflake.com/marketplace/providers/GZT0ZYQ5618/CMD%2BRVL%20%28Command%20Reveal%29)
or [Databricks](https://marketplace.databricks.com/?provider=CMD%2BRVL&sortBy=date),
or reach us at **cairn@cmdrvl.com**.

[dealcharts.org](https://dealcharts.org) ·
[Snowflake Marketplace](https://app.snowflake.com/marketplace/providers/GZT0ZYQ5618/CMD%2BRVL%20%28Command%20Reveal%29) ·
[Databricks Marketplace](https://marketplace.databricks.com/?provider=CMD%2BRVL&sortBy=date) ·
[cmdrvl.com](https://cmdrvl.com) · cairn@cmdrvl.com