Who They Are
Abacus.ai touts itself as “the world’s first cloud AI platform that handles all aspects of machine and deep learning at enterprise scale”.
Their platform empowers teams across the enterprise from IT to Marketing to Sales and more. The robust solutions available surface real-time insights using autonomous AI and machine learning.
The company, led by CEO Bindu Reddy, has its headquarters in San Fransico and received $22 million in Series B funding in late 2020. They are funded by multiple investors such as Mike Volpi from Index Ventures, Eric Schmidt (ex-CEO and Chairman of Google), Ram Shriram (board member of Google), Coatue, Khosla Ventures, and others.
What They Do
Each solution from Abacus.ai is designed to be easy to use and in some cases just point the AI engine at your data, and deep learning models will be created. Further, these models will be customized around the uniqueness of the data.
The platform capabilities include:
- Support for streaming pipelines
- Advanced data wrangling
- Realtime feature store
- State of the art machine learning models
- Plug & play your own models
- Online and batch predictions
- Explanations based on modern techniques
- Model monitoring & drift
Abacus.ai Products
AI for IT Operations: Detect the possibilities of runaway spend incidents and eliminate them even before they happen with state-of-the-art deep learning technology.
Recommender AI: Use state-of-the-art, multi-objective, real-time recommendation models to increase user engagement and revenue.
Predictive Modeling: Detect the possibilities of runaway spend incidents and eliminate them even before they happen with state-of-the-art deep learning technology.
Marketing and Sales AI: Growth Hack with AI: Convert high-quality sales leads, target personalized promotions, and reduce customer churn.
Forecasting and Planning: Deploy completely autonomous, accurate deep learning-powered forecasting and planning service in just a few hours.
Anomaly Detection: Use state of art deep learning models to spot anomalies in your data and act on them to increase revenue, decrease costs or reduce risk.
Fraud and Security: Deploy completely autonomous, accurate, deep learning-powered systems to fight fraud and keep your servers secure.
Natural Language Processing: Use state of art deep learning models to derive insights from unstructured text
Most Unique / Impactful Application
Machine Learning DevOps (MLOps) can be challenging as organizations look to scale their efforts. And, data could contain bias, be stored in data lakes, or need to be trained for embedding.
This is where the Abacus.ai MLOps solution comes into play. It’s described as a “state of the art AI platform to run your own models at enterprise scale”.
The MLOps solution is comprised of 4 key components to “accelerate in-house developed models to production, debias them, and add explainability to them“.
- Real Time ML Feature Store
- Vector Matching Engine
- Plug and Play Your Modules
- Explainable AI and Debiasing
One of the benefits of leveraging this solution is that it will help with Compliance and Governance. This is done by debiasing models from age, gender, and racial biases to ensure that you meet compliance requirements.
Who They Have Impacted
By now, many of us have heard of 1-800-Flowers.com or used its services to have flowers delivered to someone. What started as a phone-based ordering service has grown into a family of brands used by people all over.
As with any growing business, 1-800-Flowers.com was faced with streamlining personalized recommendations, email personalization and promotions, churn reduction, and fraud detection. Abacus.ai worked with the data scientists and developers at 1-800-Flowers to “deploy cutting-edge deep learning models to optimize all aspects of the customer experience within weeks“.
Amit Shah, President of 1-800-Flowers.com, stated that they can “optimize all aspects of our user experience including personalizing emails, predictive churn, and providing contextual real-time recommendations“. This optimization of their experiences provided them the momentum to become an AI-focused organization which translated into “a lift in both user engagement and revenue“.
