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Abacus.ai, formerly known as RealityEngines.ai, is an artificial intelligence (AS)-assisted data science and end-to-end MLOps platform intended to offer users real-time machine learning and deep learning at scale. Abacus.ai is developed to allow users to bring their own models or build new models using the platform's neural network and generative AI techniques for production. On the platform, these models can then be used for various enterprise AI use cases, such as churn prediction, time-series forecasting, and deep-learning-based personalization, or they can be used for specific, custom workflows based on business needs.
Abacus.ai is also engaged in foundational research in key applied AI areas to continue the development of its platform and to provide continuing features and increases in performance for users. The company was founded in 2019 by CEO Bindu Reddy, CTO Arvind Sundararajan, and Siddartha Naidu and is based in San Francisco.
Abacus.ai's platform is an AI-assisted data science platform intended to help users build applied AI at scale, with end-to-end large language model (LLM) and MLOps capabilities for enterprise use cases. This allows users to train customer models or build AI agents combined with LLMs for increased accuracy in systems and to better operationalize those systems in production.
Features include a dashboard for users' data and datasets, offering a complete picture of their data in a single place and allowing them to visualize streaming data in real time. The dashboards also allow users to evaluate models and model performance in a single place, including visualizing future predictions through those models' performance and allowing the user to see and correct model drift over time.
The platform is built to offer solutions in a variety of use cases, including personalization AI, language AI, forecasting and planning, marketing and sales, anomaly detection, AI agents, computer vision, discrete optimization, predictive modeling, and chat services.
For MLOps, Abacus.ai's platform capabilities include support for streaming pipelines, data wrangling, real-time feature store, vector matching engine, machine learning models, notebook hosting, training pipelines, plug and play for user models, online and batch predictions, and explanations for users based on modern MLOps and AI techniques.
