The last few years have seen a massive uptake of cloud computing enabling organisations to produce and store vast amounts of data at minimal cost. It is becoming more and more evident that the success of businesses depend more on how they can leverage this data to understand customer behaviour and react in real time. However, not many companies, apart from the big tech, are equipped with in-house ML capabilities to extract insights from the data and this is where Abacus.AI comes to the rescue.
Abacus.AI was founded by Google, Amazon and Uber Alumnus with vast experience in building machine learning solutions at these companies, with a mission to put cutting edge machine learning into the hands of every company and help them extract meaningful insights from their data. In order to achieve this, Abacus.AI houses a dedicated research team that invented several new neural architecture techniques. These techniques have been published as research papers at top AI/ML conferences including NeurIPs and ICML. Recently, the company applied it’s techniques and participated in the prestigious CVPR competition, Unseen Data in Neural Architecture Search and placed 2nd.
The platform features all the key components of an end to end AI service including easy set up of data pipelines, data cleaning and transformation, model training and hosting, a real-time ML feature store service, model monitoring and explainability. Abacus.AI follows the principle of keeping simple things simple, while making complex things possible. The service allows ML beginners to build and host simple ML models through an intuitive UI while advanced ML practitioners and senior data scientists can leverage APIs, write python code and SQL queries to build custom solutions
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Once trained, these models can easily be evaluated using a comprehensive model metrics dashboard, pushed to production and continuously re-trained on a regular schedule and/or whenever there is significant feature drift. Abacus.AI provides dashboards to monitor latency, traffic, errors and feature drift of models in production. This removes all the heavy lifting needed by data science teams to operationalise and run models.
Abacus.AI supports a wide range of use cases catering to the needs of different teams within your company. For instance, the predictive modelling use case can help marketing teams score leads, predict churn, the forecasting use case can help the planning team project inventory or costs better, the recommendation use case can serve your customers better by showing them the right content at the right time and the anomaly use case can help you spot risks before they cause any damage. In addition to the supported use cases, the company also let’s data science teams plug and play their models built on popular frameworks such as TensorFlow and Pytorch and let Abacus’s end-to-end AI platform take care of the rest.
The company is headquartered in San Francisco and funded by Mike Volpi from Index Ventures, Eric Schmidt (ex-CEO and Chairman of Google), Ram Shriram (board member of Google), Coatue, Khosla Ventures, and others. Their founding team of AI scientists and ML engineers have degrees (many of them Ph.Ds) from premier universities such as Stanford, MIT, CMU, UC Berkeley, Dartmouth, and IIT and have shipped high profile products at Google, Amazon Web Services, and Uber.
Their products have been adopted by world-class organisations including several Fortune 500 companies.