Documentation Index
Fetch the complete documentation index at: https://docs.deckr-ai.com/llms.txt
Use this file to discover all available pages before exploring further.
Data architecture
Deckr routes data across three specialized database tiers based on data type:SQL (PostgreSQL)
Structured financial data — ratios, loan terms, balance sheet figures, covenants. Queryable and reportable.
MongoDB
Long-form document text, news articles, court filings, and business reviews. Schema-flexible storage for unstructured content.
Neo4j (Graph)
Entity relationships — ownership structures, corporate affiliates, collateral linkages, and principal networks.
Data sources
| Source | Type | Used for |
|---|---|---|
| Uploaded PDFs | Borrower-provided | Financial statements, tax returns |
| SerpAPI | External enrichment | News and web research on borrower |
| OpenCorporates | External enrichment | Corporate registry and ownership data |
| CourtListener | External enrichment | Public court filings and litigation history |
| Yelp Fusion | External enrichment | Business reviews and reputation signals |
Enrichment pipeline
After document extraction, Deckr asynchronously enriches the deal with external data. This runs in the background and does not block the agent pipeline. Enrichment results are incorporated into the Industry Analysis and Guarantor agents.Integrations roadmap
The following integrations are planned as part of the Strategic Data Routing roadmap:- Market data — public equity tickers and trading data for publicly traded borrowers or competitors
- Prediction markets — macro risk signals from Polymarket and Kalshi
- Banking API — transaction-level cash flow data via Plaid or Finicity (with borrower OAuth consent)