For Issuers
Control how your deals and data appear across the public market. Publish your shelf context to ensure accurate, connected, and assurance-grade information.For Issuers
Control how your deals and data appear across the public market. Publish your shelf context to ensure accurate, connected, and assurance-grade information.
Take control of your market context in the AI era
You define the data that drives structured finance — but you don't control how it's interpreted, cited, or used by AI systems and analytics tools downstream.
Dealcharts lets you own your context graph — the canonical source of truth for how your shelves, deals, and identifiers appear across filings, vendors, and AI platforms.
Publish Your Shelf Context →
The data fragmentation problem
You submit filings to EDGAR, but once published, your shelf, deal names, and CIK identifiers get fragmented and reinterpreted across vendors. Trepp or Intex normalize it their way; Bloomberg assigns its own keys; AI models (ChatGPT, Claude) have no canonical "issuer entity."
Even if you publish accurate data, it's buried in PDFs. Search engines and AI systems scrape inconsistent fields — meaning your data isn't discoverable, trusted, or trainable.
Dealcharts solves this by maintaining a single assurance-grade representation of your shelf and related entities within the open context graph.
Take Control of Your Context
1. Own your shelf in the open context graph
Create a canonical representation of your shelf and series in an open, queryable graph. Relationships between deals, servicers, trustees, and funds become explicit and machine-readable.
When someone searches for "Benchmark 2025-V18," CMD+RVL's assured context becomes the authoritative reference — not a vendor's version.
2. See how your data travels
Get a unified "mirror" of how your deals appear across EDGAR, CMD+RVL, Trepp, fund holdings, and analyst coverage. Receive alerts when other entities reference your data or charts.
Visibility equals governance — you can now see and manage how your market data is used.
3. Be readable by humans and AI
All shelf and issuer data is structured, linked, and published in open metadata formats (schema.org / JSON-LD). That means your context can be read directly by models and analytics pipelines.
As AI systems interpret financial data, assured context determines whose data they trust.
Advanced Assurance & Stewardship
4. Correct or annotate your data
Add structured corrections or contextual notes (e.g., collateral updates, servicer transitions) to clarify or enrich the public record. These annotations become part of the metadata layer — not comments.
Move from static filings to living, explainable datasets.
5. Demonstrate stewardship
Provide assurance evidence — lineage, freshness, coverage, and latency — for each shelf or deal. Earn an Assurance Mark signifying transparency and data governance readiness.
This isn't branding; it's confidence. Assurance equals control.
6. Publish contextual signals
Share factual updates or market insights linked to your context graph ("Benchmark shelves show stable delinquency vs. peer group"). Enhance discoverability in both search and AI responses.
Shape your narrative with the same data others use.
7. Position for the AI future
As LLMs and retrieval systems answer investor questions directly, issuers with assured, structured data become the trusted ground truth.
Be the issuer models trust when AI systems interpret your market.
Summary
| Category | Action | Outcome | Why It Matters |
|---|---|---|---|
| Context Identity | Publish your shelf in the open graph | Canonical, machine-readable entity | Prevent misidentification and control your narrative |
| Visibility | See how your data travels | Unified view across systems | Ensure alignment and accuracy |
| Discoverability | Be readable by humans and AI | Structured, open metadata | Your data powers explainable outcomes |
| Assurance | Demonstrate stewardship | Assurance mark + lineage | Build trust with investors and regulators |
| Narrative | Publish contextual signals | Share official updates | Shape perception and discovery |
| Future Readiness | Prepare for the AI era | API-ready, assured metadata | Be the issuer models trust |
See it in action
See how assured issuer data appears in practice with real examples of canonical entity representation, structured metadata, and AI-ready context.
View CMBS Deal with Assured Issuer →
Ready to take control?
Join the issuers modernizing their data practice with assurance-grade context.
Publish Your Shelf Context →