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Real-time machine learning models are designed to accurately assess risk and drive optimal decisions
Developers First: Solving Novel and Practical Economic Problems
Building AI solutions with the Julia Language, a fresh approach to computational science and economics
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Leverage our researchers and architects to model your solution
Liquid Analytics’ Confidence AI Application: machine learning models provide a systemized approach to assess cash flow risk and opportunity.
Improve the accuracy of decision-making across your organization on your lending and payment terms and increase confidence levels
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Make decisions faster. Your teams no longer have to manually gather and analyze individual pieces of data
System learns constantly from fresh information; long term model management keeps models accurate and updating in real-time
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Augment your business flow with intelligent decisions. We help Fortune 1000 companies seize the opportunity to Experience their AI. Your data is your most valuable currency. Change the way you think about managing people, creating products, and experiences, generating revenue and reducing costs.
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This 15-minute podcast discusses just how crucial Knowledge Graphs are becoming for your organization's bottom line, and why they should be considered as a preliminary investment to digital innovation.
There is no time to slow down during a global pandemic; we have to remember that commerce still makes the world go ‘round. Leveraging machine learning models and becoming a data-driven enterprise enables you to navigate in a highly risk-averse ecosystem.
Neural network (NN) models are the brains that comprise AI algorithms. These models are inspired by how a human brain processes information to identify things. While the growing number of available models is staggering, there are several standard models which are used as a starting point when designing more complex models.
Data lakes are beginning to represent the heartbeat of organizational operations and hold the key to optimizing your workflow, while also making data-driven strategic decisions that are powered by AI.
AI and machine learning are best-suited to specific types of tasks and these vary in complexity. For this reason, it is important to determine what you’re looking to accomplish so that you can intelligently configure and aggregate your data for the AI process to produce favorable results.
Given current business volatility, customers want immediate solutions and the question is: As a Business Process Outsourcer (BPO), is AI right for you, now?
As more businesses are incorporating AI and ML into their strategy to reduce costs and create better products, they are gaining a competitive advantage over those holding on to traditional means of operation. Employed effectively, AI and ML will provide tide-turning returns for companies. If you’re looking to introduce AI into your business strategy, how do you choose the most effective business cases? How do you measure the empirical value?
As AI is increasingly adopted globally, it is vital to consider how AI can bolster your business. Gartner predicts that by 2020, 85% of customer interactions will be managed without a human. While AI is no silver bullet, when applied effectively, it can enable businesses to tune their customer interaction, marketing, and product design to competitive levels.
The most disruptive force in marketing today isn’t what you think. It’s not a machine. It’s not a device. It’s not an AI interface or a machine learning model or a conversational assistant. It’s the consumer. More specifically, it’s what consumers have come to expect from their brands. And if you can’t meet the needs and preferences of the next-generation consumer, your brand won’t stay relevant for long.
The surest way to grow your brand’s market share is to engage with consumers in a personal and meaningful way. By personalizing UX on every level, businesses give themselves the best chance at scaling their growth. But how do they do this in the realm of eCommerce, where there is often no human-to-human interaction?