Why do we change things?
We might be just fine, but we see an opportunity, or a threat, on the horizon and it changes the way we see the world. When the world changes, we change to. As humans, we have evolved and adapted according to our environment. When we don't, we miss an opportunity, or we face a threat.
We launched BatNav in 2020 to help buyers of energy storage systems find sellers of energy storage systems. But we were commited to doing it differently. We were, and still are, committed to using technology to automate the delivery of project services. We had insight into state-of-the-art text generation and could see where the world was heading.
In 2020, most people didn't really get it. But we didn't care. We knew the opportunity, and the benefit, was huge. We knew that by automating the analysis, drafting and formating of project deliverables, we could free people from work that added no value, so they could focus their creativity and intellect on work that would. And we were also passionate about the energy transition and the role of energy storage in delivering it.
We had an ambitious roadmap. We had many successes, and plenty of failures. That's the nature of a technology startup. Typically, a technology startup takes about 4 years to find product-market fit before making meaningful revenue. That's a long time for a team to keep working on something that isn't working, and pay the bills at the same time.
During that time, the world changed. Text generation capabilities exploded with the widespread availability of generative AI in the form of large language models (LLMs) like ChatGPT, Claude, Llama, and others. Ecosystems of models and datasets seemed to grow exponentially. Generative AI services were accessible and affordable. Generative AI models with comparable performance to the best models were available to privately host in a secure server to ensure confidentiality of sensitive data.
When there is a step change in technology, the world changes with it. Windmills used to grind wheat into flour. Ponies pulled barges in canals to transport goods across England. Horses and bullocks pulled carts and wagons. The steam engine replaced wind and ponies. And the internal combustion engine replaced horses and bullocks. Now, generative AI is the new engine and we need to build arount it.
So that's what we did. We made a decision: rebuild our technology around LLMs. Last year, we did a teardown of our technology. Imagine a teardown of a car. You pull everything apart. You lay out all the parts on the floor. You look at what you've got. We had already made so much progress in learning how to automate project services, now we had a hugely powerful and productive new engine. So we built around it.
As we built, we saw the potential for new use cases.
As we told people about it, we heard about how they would use our technology to solve their problems:
As we got more confident, we thought "let's think bigger". And change happened. We are still true to our commitment to helping people deliver the energy transition. Instead of helping people deliver energy storage technologies, we will help people deliver energy transition technologies.
And with this change, we have more exciting news that we will share soon.