There’s a change in the air, and it seems companies need to think about how to implement great language models, but as with any new advanced technology, that’s often easier said than said. do, especially for less technical organizations.
AirOps, an early-stage startup, is in the right place at the right time, helping companies take advantage of these new capabilities to build AI-powered applications on top of large language models. Today, the company announced a $7 million seed round, which actually closed early last year.
The company’s CEO and co-founder, Alex Halliday, said with the recent interest in LLMs, there is a challenge for companies trying to get involved. “There’s a really big gap to bridge between these amazing capabilities that people can play with in things like ChatGPT, and then [applying that] to the toughest kind of business challenges. So we’re creating a platform that lets people come in and build custom solutions on top of those algorithms that really move the numbers in the business,” Halliday told TechCrunch.
The company currently helps customers build applications on three LLMs: GPT-4, GPT-3, and Claude. The idea is to help users do things like automating processes, extracting insights from data, generating personalized content and performing natural language processing techniques, according to the ‘business.
Halliday says current customers are looking for ways to leverage their own data and content in conjunction with LLMs to create new content from that existing corpus or create a generative AI experience on top of their existing software.
One of the company’s main value propositions is to help customers use these models more effectively and efficiently, as this can be expensive. “What’s really interesting is that you can actually use the larger models to train smaller models. So maybe for the first two months you would use GPT-4, and that would create the outputs of training to then use a smaller open source model that has been refined,” he said.
And AirOps can help you get through those steps. “We’re really learning the right recipes and architectures here, but we expect that over time the boil-the-ocean, sledgehammer type of approach will give way to a more nuanced and better understanding of how to take advantage of the menu of choices people have,” he said.
The company was launched last year to help leverage its organizational data, but as LLMs entered the public consciousness, the company changed direction. “As we began to look at the application of LLMs to the data space, we realized that actually a much bigger opportunity was to help people combine LLMs with their data to create workflows. and custom apps,” he said. Last fall, they really focused on this approach.
The company has 14 employees with a few open positions. Halliday says he sees diversity across many dimensions, but he aims to build a diverse employee base as he builds the company, and that’s especially true given the size of newcomers. LLM. “We really showed great openness when hiring people with different backgrounds and levels of experience,” he said.
The $7 million seed investment was led by Wing VC with participation from Founder Collective, XFund, Village Global, Apollo Projects and Lachy Groom.