As artificial intelligence becomes more integrated into daily business operations, accuracy and security are no longer optional, especially in the private credit space, where confidential, complex data is the norm. Generic, open-source AI tools are not built to handle the nuanced demands of this sector, and entrusting them with sensitive information poses significant risks.
At Street Diligence, we recognized this early. That’s why we built SD Chat, a proprietary large language model (LLM) engineered specifically for private credit. Unlike general-purpose models trained on broad internet data, SD Chat was developed using a decade’s worth of curated, thousands of private credit data points, gathered from real-world agreements and structured for optimal reasoning and reliability.
Trained for Private Credit
Other models attempt to generate answers on the fly without the benefit of a structured knowledge base, often relying on guesswork or probabilistic reasoning. This can lead to unreliable outputs, especially when handling technical financial queries.
For example, if you were to ask a generic model, “What is my RR on this deal, given that the Japanese yen is 300 to one?”—the model would need to infer multiple missing facts: the closing margin interest, the penalty fees, and other contextual data. Without foundational domain knowledge, this increases the chance of errors.
In contrast, SD Chat already knows the critical facts. Trained on a deep base of structured private credit knowledge, our system doesn’t need to invent or infer; it retrieves, reasons, and cites with confidence. That means fewer assumptions, more precision, and faster answers.
Built-In Tools for Advanced Analysis
SD Chat isn’t just a language model, it’s a reasoning engine equipped with internal tools. When a user submits a query, the model can:
Retrieve related concepts from a structured ontology,
Rank and compare results against pre-augmented knowledge,
Use calculators and internal logic to generate complex, multi-step answers.
In addition to providing direct responses, SD Chat integrates Street Diligence’s proprietary analytics, such as scores, prevalence metrics, and favorability indicators, giving users deeper insight into the strength and relevance of particular clauses or concepts within an agreement.
Unmatched Transparency Through Citations
One of SD Chat’s most powerful differentiators is its ability to cite the source of its answers. For every response, the model identifies the exact contract clause or term where the answer was found. Whether the information is from one of our 300+ tagged terms or a previously untagged section, SD Chat highlights the relevant excerpt—giving users confidence in both the origin and accuracy of every output.
The Future of Private Credit Intelligence
With countless AI tools emerging in the market, it’s easy to get caught up in hype. But only SD Chat combines deep, curated private credit knowledge, advanced reasoning tools, and citation-based transparency. This is the result of years of focused research, refined training, and a relentless commitment to accuracy.
As we continue to expand our library of structured data and evolve our agent-based tools, SD Chat will keep setting the standard for AI in private credit, delivering smarter answers and more powerful insights.