We take a practical approach to environmental responsibility that reflects how ResearchRabbit operates today. We are a small team of 9 people, so we try to stay realistic about the scale of our impact and focus on practical choices in how we work. However, we still consciously do the best we can. 💪
Our focus is on thoughtful design choices, efficient systems, and avoiding unnecessary compute-heavy features.
ResearchRabbit does not use large language models to power its core recommendation and discovery systems. Instead, we use graph mathematics, old-school server infrastructure, and a little bit of pre-processed magic. ✨
What we currently do as a team
We prioritise remote work and flexible working to reduce commuting-related emissions.
We use shared office spaces when in-person collaboration is useful, rather than maintaining permanent private offices.
We support international and distributed hiring, which reduces the need for relocation and frequent long-distance travel.
We operate with digital workflows and do not rely on printing.
We build ResearchRabbit to support better research. This is why we prioritise efficient infrastructure and avoid adding resource-intensive features that do not clearly benefit researchers.
You can read more about how ResearchRabbit works here:
How we use AI