Transforming GenAI Hype to Reality

The topline numbers are astounding. Bloomberg claims there is a $1.3 trillion market opportunity by 2032. ChatGPT saw 1.7 billion visits in November of 2023. The number of users to ChatGPT exceeded 100 million — a number that took the internet seven years to hit. From headlines to the reality, it’s clear that generative AI has become the most hyped technology in decades.  

Yet, if we look back in time to the last major technology to experience this kind of explosive promise, it would be the internet. At the time, it was the promise of democratizing information, of distributing computing, of networking people in limitless way, which all gave way to massive, economic transformations.  

Today, with generative AI tools, we can see a democratization of expertise. ChatGPT launched just a bit over a year ago, and the many ways that this will play out inside of an enterprise are still being determined. Indeed, when we speak with a large company three things are immediately apparent:  

1. Beyond the hype, enterprises want to understand the tech. Often they ask “how does this actually work,” “in what scenarios does this work,” or even more to the point for an enterprise, “does this really work?”

2. Then, after that first layer of information, they want to understand how companies are truly deriving value from AI — how we’ve worked with large firms to transform a nascent, hallucinating technology into real business value.  

3. And the final level comes down to once the technology is in their landscape, how can they leverage it to then solve other business problems?

We’ve built hila Enterprise to address each of these concerns. The technologies today, specifically the large language models, are remarkable but still have some crucial flaws that inhibit their ability to truly be useful for enterprises. To address these, we’ve built core capabilities, including text2sql to query structured data, multiple anti-hallucination features, advanced data extraction for tables, charts and metadata, and a flexible deployment structure for any enterprise’s cloud or system of record.  

Next, we’ve built ready made applications, such as Conversational Finance, and have partnerships with KPMG and Cognizant to bring them into an enterprise rapidly, delivering real business value in 90 days on a variety of finance, supply chain management and legal use cases.  

Then, finally, we offer our platform for a company to build and monitor its own generative applications with these various components — ingesting any type of data, then providing true business value with an AI layer.  

Let me provide an example: for a major energy company, our system analyzes thousands of contracts, extracts dozens of key legal terms, eliminates hallucinations and completes  a “first pass” for legal agreements, previously done by junior lawyers or outsourced. It does all of this within a half hour, whereas the manual processes of the past could take months of labor by dozens of employees.

In this way, we’ve helped many companies transform the generative AI hype into reality.  

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