Looking to empower businesses with comprehensive, real-time insights into individual companies’ credit profiles, martini.ai, the AI-driven credit analytics firm has launched Agentic AI Company Research.
By merging credit spread data with essential corporate information, Agentic AI Company Research by martini.ai provides decision-makers — including those in private credit — with data-rich intelligence that highlights key trends, risks and opportunities. The new offering combines daily credit risk modelling with agentic research to provide a dynamic, 360-degree risk assessment.
“In today’s fast-paced financial markets, access to timely, integrated information is crucial for effective risk assessment,” said Rajiv Bhat, CEO of martini.ai. “With Agentic AI Company Research, our customers — particularly in the private credit space — gain a clearer picture of each company’s credit health, enabling them to move faster and make data-driven decisions with confidence in a sector often challenged by poor disclosures, lack of traditional credit ratings, and the need for intensive due diligence.”
The market is currently experiencing trouble with financial l transparency, high default risk, and resource constraints. With Agentic AI Company Research, martini.ai offers a streamlined and scalable way to identify and monitor risk across a wide range of private companies. Notably, all martini.ai requires is the borrower’s name, and in just a few minutes, the platform delivers an independent signal on a company’s credit risk.
Agentic AI Company Research is the latest addition to martini.ai’s expanding suite of credit analytics solutions, designed to help financial institutions, investment managers, and corporate decision-makers optimise their risk management practices — especially crucial for private credit investors who require more visibility into portfolio risks.
Benefits
The new martini.ai offering provides a variety of benefits for its users. Notably, it situates each company alongside up to 100 peers, drawing on all available market data and applying advanced graph algorithms to estimate the probability of default for over 3.5 million companies every day. This continuous modelling is especially valuable in private credit, where data can be sparse, and speed is essential for managing risk in illiquid portfolios.
Furthermore, it builds upon these quantitative insights by orchestrating multiple advanced large language models (LLMs) with relationships and insights from martini.ai’s knowledge graph. This comprehensive approach synthesises over 30 distinct points of research, capturing each company’s history, key events, sector and micro sector developments, competitor analysis, macro factors, benchmarks, and the latest news — all in one cohesive view.
By layering in the nuances of private credit markets, agentic research offers a richer perspective on emerging risks and opportunities.
Portfolio managers are also in line to benefit from the new offering:
- Reduce losses by 50 basis points: Early identification of potential defaults through martini.ai’s platform can significantly decrease portfolio losses.
Increase yield by up to 100 basis points: Rapid identification of high-yield deployment opportunities enhances returns. - Decrease portfolio monitoring time by 85 per cent: Evaluate a portfolio of 500 names in just 30 minutes, freeing up valuable time for strategic decision-making and higher-value activities.
- Receive fast, independent credit risk signals: Access near-instant analysis by simply providing the borrower’s name, expediting credit decisions.
