Synnax delivers forward-looking credit intelligence by aggregating machine learning model predictions through a decentralized consensus mechanism. The platform provides real-time financial ratio predictions, probability of default scores, and company status assessments for both private and public entities. This credit intelligence enables companies to demonstrate creditworthiness securely, potentially lowering funding costs and accessing new credit sources.
Funding
$550K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional credit rating systems often suffer from biases and lack real-time insights, especially for private companies with limited data transparency. These systems struggle to provide accurate and timely assessments of financial performance, hindering access to capital and increasing the cost of funding.
Solution
Synnax offers a decentralized machine learning network that delivers real-time, unbiased credit intelligence by aggregating financial performance predictions from multiple models. The platform uses advanced, privacy-preserving data exchange protocols, including homomorphic encryption and data obfuscation, to allow private companies to demonstrate creditworthiness while protecting sensitive information. For public companies, Synnax analyzes a vast and continuously updating dataset to provide financial ratio predictions, probability of default scores, and company status predictions. This approach provides a broader perspective beyond traditional credit ratings, offering a more accurate and forward-looking assessment of creditworthiness.
Target Audience
Synnax targets private and public companies seeking to demonstrate creditworthiness, access previously untapped sources of credit, and lower their cost of funding, as well as data scientists interested in contributing to the platform and earning revenue.
Features
- Decentralized, bias-resistant consensus mechanism that aggregates ML model predictions
- Real-time financial ratio predictions, probability of default scores, and company status predictions
- Advanced, privacy-preserving data exchange protocols, including homomorphic encryption and data obfuscation
- Support for both private and public company data
- Synnax ZK/e platform for discreet data validation, allowing companies to prove asset balances without revealing sensitive information
- Synnax Lab, a platform where data scientists can solve financial challenges and earn revenue shares