The Environmental Impact of Brainfish’s AI

Curious about the environmental impact of Brainfish? It's far less than you think. And in a world where AI is becoming the norm, it’s a point worth diving into.

When we talk about AI's carbon footprint, the conversation is often focused on just one part of the story: model training. This is the process of teaching a large language model using huge datasets, and it requires a staggering amount of energy. To give you some perspective, a single major AI model training run can have a carbon footprint equivalent to hundreds of thousands of miles driven by a gasoline-powered car.

However, once a model is trained, running it (inference) is a different story.

The majority of our energy usage comes from running inference on pre-trained models.

This is far less energy-intensive, similar to the energy consumption of any standard SaaS application. We don't train new foundational models from scratch for each customer; we use models that have already been trained, making Brainfish incredibly efficient from a power perspective.

As researchers have noted, the energy required for inference is dramatically more efficient than for training, making it akin to the power usage of a simple web search. We're a customer-centric company, and that extends to being an environmentally-conscious partner. We do have “fish” in our name, after all.

Our Responsible AI Philosophy

We believe that truly innovative technology should not come at the cost of sustainability. From day one, our team has been focused on building a platform that is not only effective but also thoughtful in its design and footprint.

This is why we focus on leveraging small, pre-trained models. While larger, general-purpose models require massive, continuous training, our approach is more surgical. We've built Brainfish to solve a very specific problem: transforming your internal knowledge into a powerful, automated resource, and making it easily accessible to your team and customers. This narrow focus allows us to operate with a fraction of the energy and computational resources of a large AI company, a direct outcome of our commitment to responsible development.

Our commitment extends to our infrastructure as well. We run on Amazon Web Services (AWS) in the US East region. AWS has made its own significant commitment to sustainability, including a target to match 100% of the electricity used across their global operations with renewable energy and a goal to be "water positive" by 2030, returning more water to communities than their data centers consume.

It’s Only the Beginning

The conversation about AI and the environment is just beginning, and it's one that every company leveraging AI should be having. We believe as an industry, we have a responsibility to not only build powerful technology, but to do so consciously.

We are proud to be a part of the solution, showing that it's possible to deliver immense value without a massive environmental cost. Our model for responsible development proves that an intentional, philosophical approach can lead to a more sustainable, more efficient future for the entire tech landscape. We welcome this conversation with our customers and look forward to continuing to build technology that is both brilliant and responsible.