AI and Data-Center CMBS Exposure Tool: Filing-Backed Coverage

DealCharts now has a focused way to check whether a CMBS CUSIP, list of CUSIPs, or fund ID touches the current data-center and AI-industry exposure index.

The tool is intentionally narrow. It reads coverage metadata from public filings and DealCharts deal records. It returns theme counts, named tenants when available, peer fund counts, the unique deals behind the CUSIPs, and per-CUSIP detail. It does not produce risk scores, ratings, or verdicts.

Use the interactive CMBS exposure tool when you want to paste a fund ID or CUSIP in the browser. Use the CMBS AI exposure list when you want the deal-by-deal view.

What the Tool Covers

The coverage index is built around disclosure-backed themes that matter when structured-finance teams are screening commercial mortgage pools:

• Data Center: a data center appears in the collateral pool.
• Tech Giant: Google, Microsoft, Apple, Amazon, or Meta is named as a tenant.
• Cloud and SaaS: IBM, Oracle, Salesforce, or Snowflake is named as a tenant.
• Software Leaders: Tesla or Palantir is named as a tenant.
• Chip Manufacturers: NVIDIA, Intel, Broadcom, Qualcomm, or TSMC is named as a tenant.

Those labels are coverage tags. They are not claims about credit quality, rent durability, refinance risk, market demand, or tenant performance. The useful part is the trace: a theme points back to a CUSIP and deal, and the deal page carries the related collateral, servicer, party, and filing context.

Query the Endpoint

The same coverage snapshot is available as JSON with no login and no API key.

GET https://dealcharts.org/.netlify/functions/exposure_to_tech?input=065923AY0

You can pass a single CUSIP, a comma-separated CUSIP list, or a fund ID.

curl "https://dealcharts.org/.netlify/functions/exposure_to_tech?input=065923AY0"
curl "https://dealcharts.org/.netlify/functions/exposure_to_tech?input=065923AY0,36258RBA0"
curl "https://dealcharts.org/.netlify/functions/exposure_to_tech?input=S000028163"

The response shape is stable enough for analyst notebooks, screening scripts, and AI retrieval workflows:

• input

  : the detected input type and normalized value.

• fund

  : fund context when the request is a recognized fund ID.

• aggregated_results

  :

  total_cusips

  ,

  total_themes

  ,

  tech_theme_count

  ,

  theme_counts

  ,

  total_peer_funds

  ,

  unique_deals

  ,

  tech_tenants

  , and a no-score note.

• individual_results

  : per-CUSIP deal name, themes, tech themes, peer fund count, and tenant names when available.

• metadata

  :

  source_files

  ,

  requested_count

  ,

  processed_count

  ,

  missing_count

  ,

  missing_cusips

  , and

  as_of

  context when available.

This is a public read surface, not an admissibility API. Treat it as a fast way to find the filings and deal pages worth reading next.

How Structured-Finance Teams Use It

The immediate use case is triage. A portfolio analyst can paste a fund ID and see whether the fund currently maps to covered CMBS CUSIPs. A data engineer can pass a list of CUSIPs from a holdings file and keep the response in a reproducible notebook. A credit or research team can use the deal list to open the underlying DealCharts pages and review the filing context.

The tool also gives AI agents a cleaner citation path. Instead of asking a model to infer whether a deal has data-center collateral or AI-industry tenants from broad web text, point it at the JSON endpoint and require it to cite the CUSIP, deal name, theme fields, and DealCharts page it used.

What It Does Not Do

The exposure endpoint does not rank deals, score tenants, predict losses, or tell you whether an exposure is good or bad. It does not replace a surveillance model, a credit memo, a rent-roll review, or a committee decision.

That restraint is deliberate. DealCharts is the public projection layer for crawlable, citable structured-finance data. It surfaces coverage, provenance, freshness, and links back to the relevant data surfaces. Evidence adjudication and final decisions belong in the downstream Signals and Evidence workflow.

Start with the Live Surfaces

For a browser workflow, open the AI and Data-Center Exposure Tool. For the deal list and theme definitions, use the CMBS exposure hub and the AI exposure deal page. For bulk work across the wider public corpus, start from DealCharts datasets and

llms.txt