
sabbi
Turn-key machine learning and AI decisioning platform.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor | €0.0 | round |
KRW1.0b | Series A | ||
Total Funding | 000k |
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Sabbi, also known as SavviHub, provides a turn-key solution for businesses aiming to leverage their data through artificial intelligence and machine learning. The platform is designed for machine learning and data engineers, taking them from data collection to deploying actionable, ML-powered decisions. The company operates in the developer tools, MLOps, and artificial intelligence sectors.
Founded in 2020, the company targets businesses that need to make data-driven decisions in real-time. Its business model is centered on providing a comprehensive, end-to-end tool that simplifies the process of building and deploying AI applications. The platform emphasizes speed, security, and scalability, offering features like model transparency, dynamic decisioning against thousands of real-time options, and the ability to start without pre-existing clean data. For security, it uses a single-tenant architecture with client containers to ensure data is isolated and encrypted, and it is SOC 2 certified. Clients can host the solution within their own virtual private cloud or on-premise.
A key feature is 'SAVVI Sheets,' a no-code tool that allows users to simulate decision outcomes with their data without needing development resources. The platform is designed to be goal-oriented and results-driven, providing practical insights and trackable results to improve business workflows. It ensures that machine learning models are not 'black boxes' by offering transparency and explainability, allowing clients to audit decisions and understand which data influences outcomes.
Keywords: machine learning platform, AI solutions, data engineering, developer tools, MLOps, real-time decisioning, no-code AI, model transparency, data security, SOC 2 certified, scalable AI, on-premise AI, end-to-end machine learning, data insights, business intelligence, AI applications, data-driven decisions