AirOps is helping companies build AI-enabled applications on top of LLM

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It feels like there’s a change in the air and companies need to figure out how to make large language models work, but like any new advanced technology, it’s easier said than done, especially for less tech-savvy organizations. It’s difficult.

Early-stage startup AirOps is in the right place at the right time to help companies take advantage of these new capabilities to build AI-enabled applications on top of large-scale language models. . The company announced a $7 million seed round today, but it actually closed early last year.

The company’s CEO and co-founder Alex Halliday said the recent interest in LLMs presents challenges for companies trying to get involved. “There is a huge gap between these amazing features that people can play with something like ChatGPT,” he said. [applying that] For the kind of toughest challenges in business. So we’re creating a platform where people can create custom solutions on top of these algorithms that actually drive business numbers,” Halliday told TechCrunch.

The company currently helps customers build applications on top of three LLMs (GPT-4, GPT-3 and Claude). The idea, according to the company, is to help users automate processes, extract insights from data, generate personalized content, perform natural language processing techniques, and more.

According to Halliday, current customers are leveraging their own data and content in combination with LLM to build new content from existing corpora or build generative AI experiences on top of existing software. looking for a way

One of the company’s main value propositions is to enable customers to use these models more efficiently and effectively. “What’s really interesting is that you can actually use the big model to train a small model. So for the first few months we’re going to run with GPT-4 and that’s how we create the training output and fine-tune it. We will use a smaller open source model that has been developed,” he said.

AirOps can help you take these steps forward. “We’re really learning the right recipe and architecture here, but as time goes on, the sledgehammer-like approach that boils the sea becomes more and more about how to leverage a menu of choices.” I hope it will be superseded by nuanced and better understanding.People have,” he said.

The company launched last year with the goal of helping organizations extract value from their data, but as LLM has moved into the public consciousness, the company has shifted its focus. “When he started looking at the application of his LLM to the data space, he realized that there was actually a much greater opportunity for blending LLM with data to create custom workflows and applications. he said. Last fall they really shifted focus to that approach.

The company has 14 employees and several open roles. Halliday says he sees diversity in different dimensions, but he aims to build a diverse employee base when building the company. “We have been very open-minded in hiring people from different backgrounds and different 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.