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One of the biggest challenges AI researchers and developers face is working with unstructured data. Unlike structured data, which is organized and easily searchable, unstructured data has no pre-defined model or organizational system and is often difficult to analyze using traditional methods. However, as the amount of unstructured data in the world continues to grow exponentially, it is essential to be able to extract insights and knowledge from this data.
Commerce.AI is poised for customers to tackle their unstructured data challenges. The startup leverages the latest advances in natural language processing (NLP), computer vision, and machine learning technology to deliver an AI-powered platform that helps businesses make data-driven decisions. The platform offers solutions that enable businesses to optimize product data, conduct market research, and understand consumer feedback. With industry-specific taxonomies, customized dashboards, and customizable alerts, Commerce.AI provides insights and analytics that help businesses make data-driven decisions.
Hear Andy Pandharikar, Founder and CEO of Commerce.AI, How His Startup Can Understand Unstructured Text, Voice, and Video Data, and Helping Customers by Working with Microsoft I asked for some insight on how the confidence came about.
Harness the value of unstructured data
Commerce.AI was founded with a mission to harness the power of AI to change the way commerce is done. Andy’s previous startup focused on using data to help fashion retailers improve product sizing accuracy. After the acquisition, Andy and his team began investigating other scenarios where unstructured data could yield valuable insights. And as he made clear, there was certainly no shortage of data to work with.
“There are 24 quintillion bytes of data created every day, or a billion bytes,” says Andy. “And his 90% of that data is unstructured.”
This unstructured data is a potential goldmine of insights about customer sentiment, market trends, usage patterns, and other information that can be used to make better decisions. However, unstructured data is more difficult to analyze than structured data, and companies often struggle to make good use of it.
“There’s a lot of value out there if companies can access it and understand it,” says Andy. “When I ran my first startup, I found fitting to be a big problem in fashion. , how would you predict what kind of clothing you would produce? Our data predicted what size would fit.”
Gain customer trust with Azure and OpenAI Service
With his company’s mission to help businesses make data-driven decisions using advanced AI, NLP techniques, and machine learning algorithms, Andy believes Commerce.AI stands out from other products in the space. to clarify what is different.
“We are an AI-first company,” he says. “The way we differentiate from our competitors is by focusing our infrastructure on AI. It’s related.”
“Large Scale Language Models (LLMs) like OpenAI are very good. Other startups have the ability to adapt existing models to meet customer needs rather than building their own.” I encourage you to find a field.”
The company starts by defining a customer’s business problem, then develops a solution approach and tailors its AI infrastructure to those needs. As a startup, Commerce.AI realized that it could not match the computing infrastructure of the big cloud companies. This led them to Microsoft Azure.
“When we started using the Azure infrastructure, we had tremendous confidence in its security, scalability, and compliance,” says Andy. “I realized that it leads to customer trust.”
Also, Azure provided more than just infrastructure. As part of the Microsoft for Startups Founders Hub, Commerce.AI Azure OpenAI Service (AOAIS) Beta program after testing Chat-GPT3 internally for over a year. This service allows us to provide our clients with generative insights instead of tables and text, eliminating the need to program from scratch. Example: You may want to summarize a long customer service call with the goal of creating a better script for agents to refer to in the future. Azure OpenAI Service can look at its overview and other past scripts to develop something that resonates with customers.
“We are an applied AI company, so when we solve problems, we are always looking at what is out there and being open. The tools and infrastructure are out there, and our partnership with Microsoft gives us great confidence in delivering these capabilities to our customers, so when we talk about trust, security, compliance, and scalability, they are the Azure OpenAI Service It’s all about how it’s enhanced by
Andy’s advice to other startups? Don’t try to rewrite the book when it comes to AI.
“Large-Scale Language Models (LLMs) like OpenAI are very good,” he says. “I encourage other startups to find areas where they can adapt existing models to meet customer needs rather than building their own.”
There have been significant advances in the LLM field in recent years, especially since the introduction of transformer-based architectures such as BERT, GPT, and T5. These models have pushed the boundaries of natural language understanding and generation and have led to several breakthroughs in language-related tasks such as pre-training, transfer learning, multimodal learning, and interactive models.
There are hurdles to clear for startups looking to use LLM, such as the sheer amount of high-quality data needed to make it work effectively, and Andy suggests using pre-trained models. That’s why.
“Instead of trying to rebuild your OpenAI infrastructure, spend your time and resources using it in ways that work for your customers,” says Andy. “The OpenAI models are really great. You can’t beat them.”
It was clear from our conversation that Andy sees tremendous value not only in Azure OpenAI services, but also in membership in the Microsoft for Startups program. Andy expressed his enthusiasm for the infrastructure and strategies provided by the Azure team and Founders Hub.
“Cloud credits can help you in the early stages to deploy and test different strategies and do free POCs,” says Andy. “But once the product starts to achieve his market fit, it also requires a good go-to-market strategy.”
According to Andy, working with Microsoft’s go-to-market experts, sales, and customer success team members helped Commerce.AI understand its strategy, paving the way for momentum and scale. And since many of our customers already have their own cloud infrastructure on Azure, it’s easy for Commerce.AI to deploy a solution.
For more tips on bringing AI to your startups and accessing AI services in Azure, sign up today for the Microsoft for Startups Founders Hub.
Tags: AI Infrastructure, AI Researchers, Commerce.AI, Data, LaunchWithAI, Predefined Models, Startups, Unstructured Data