5 Generative AI Companies That Will Change The Future Of Work

By Lawrence Wang

Given the current economic climate, businesses are acutely interested in reducing costs, increasing efficiencies and exploring new growth opportunities. Technological innovations to optimize existing processes could dramatically increase a company’s bottom line. The launch of OpenAI's ChatGPT in November 2022 marked a turning point in how Generative AI can be used in the workplace - setting off a wave of change in how we work.

Generative AI is powered by models (e.g. algorithms and architectures) trained on a trove of data that is gathered through public domains. With this data, these Generative AI models are able to learn patterns, structures, and relationships, enabling them to generate new content and ideas based on their acquired knowledge. Although the underlying infrastructure behind Generative AI models have been around for many years, through an easy-to-use user interface, OpenAI’s ChatGPT has enabled more knowledge workers to gain access to this technology. Under the hood of any Large Language Model, which is what powers ChatGPT, transformers use self-attention to predict the next word in the sentence. This allows the model to come up with answers that are coherent to the average person.

Generative AI is powered by models (e.g. algorithms and architectures) trained on a trove of data that is gathered through public domains. With this data, these Generative AI models are able to learn patterns, structures, and relationships, enabling them to generate new content and ideas based on their acquired knowledge.

Given how easy it is to use Generative AI models and the fact that the compute costs have decreased drastically over the last few months, more and more startups are leveraging them to create Generative AI applications for office workers. From summarizing video calls to automatically creating marketing copies, here are five companies that are able to improve our day-to-day workflows.

Guru AI

Guru is unique on this list in that it uses cutting edge vision models instead of Large Language Models to allow developers to quickly create interactive video AI products. Guru has an out-of-the-box model that makes it simple to analyze user motion in videos. Not only is it able to recognize the specific movements of people, and objects, it is able to understand what actions they are taking. For example, swinging a golf club or walking up a flight of stairs. It also gives developers the capability to conduct time series analysis - counting the number of reps an action is taking place or trimming a video to identify specific segments of motion. With Guru, professionals no longer have to just describe how to do a movement, but can show the specific visual markers on the video - allowing the recipients to truly understand and mimic said movement.

So how can businesses use Guru? A physiotherapist could create an app that performs custom physical therapy assessments virtually, correcting patients on how best to do certain exercises. A basketball team could use it to compare and contrast how different players are shooting 3-pointers - pinpointing exactly what players are doing down to each specific movement.

So how can businesses use Guru? A physiotherapist could create an app that performs custom physical therapy assessments virtually, correcting patients on how best to do certain exercises. A basketball team could use it to compare and contrast how different players are shooting 3-pointers - pinpointing exactly what players are doing down to each specific movement.

Loopin

Loopin records and summarizes video calls, allowing teams to focus on what matters instead of taking notes during these meetings. After the meeting ends, it automatically sends a meeting summary to each participant on what was discussed and lays out the action items as next steps as well. What differentiates Loopin from other similar tools is that it’s able to connect the dots between meetings – allowing teams to review notes from related meetings without going through other applications.

Refact

If you’re a software engineer, refact would definitely speed up the software development cycle. Not only does it suggest code as you’re writing, but it also identifies code that can be optimized – making it easier to understand. Refact also has the ability to analyze your code and provide documentation on what the lines of code are supposed to do. There is also an AI Chatbot that you’re able to converse with about the code in question – allowing anyone to get a better understanding of the syntax of the code given a specific context. This is especially helpful for junior engineers or students who are just learning how to code.

Alicent

Alicent is a Chrome Extension that is able to take on different roles as powerful AI assistants. It is able to generate highly specific texts for different use cases such as writing social media posts or landing page copies. Alicent stands out in that it can scan through any piece of content and provides a tailored summary of that page with the voice of the AI assistant. Marketers for a retail brand can instantaneously come up with email copies just by scanning their own product pages – coming up with tailored descriptions for each product in their inventory.

Marketers for a retail brand can instantaneously come up with email copies just by scanning their own product pages – coming up with tailored descriptions for each product in their inventory.

Fabric

Fabric is a unified collaborative workspace, the command center of all your files - solving digital clutter and chaos. It uses semantic search to look through all your files and enables you to find what you need even if you don’t recall exactly where it is. You’re able to instantaneously save content from a website, make a note of it and share with your coworkers as well.

So what’s next?

The five startups mentioned above are just a few of the many companies that employ Generative AI to enable employees to be more productive - automating work that would have taken a lot more time or resources to accomplish before. As the technology matures, I envision a future where each one of us will have numerous AI helpers in many facets of our professional lives. This will reduce the amount of time spent on the mundane and routine work we have to do, while empowering us to do work that we truly enjoy and is truly value-add.

Lawrence Wang (’19) is a Columbia Business School Alumnus. He is the founder of Butter Data, a B2B Saas product that automates data science for non-data teams – with the mission to democratize data insights for all. Prior to starting the company, he led Data Science for Community Commerce at Instagram and Facebook Shopping. Lawrence started Butter Data due to his belief that every single employee should have access to data driven insights instantly to make better decisions. He believes AI will transform the way we work, augmenting and optimizing our existing workflows.