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wildflow docs

Path there

On a path of accelerating towards a comprehensive understanding of nature and aligning human activities with it, we have these obstacles:

  1. Limited understanding of nature itself (top priority) – We will pioneer foundation models for biodiversity to help us understand nature better (and utilise data better). We’ll start collecting simple statistical models in one place and making them accessible. We don’t want to be a bottleneck for biodiversity researchers and tell them what to do. Instead, we will empower them with cutting-edge AI and data tools.
  2. Slow response and research – we will be accelerating research and response to environmental threats by optimising existing processes and doing heavy data lifting for ecologists (so that we create marine protected areas in months, not in 5 years, etc). Building custom solutions for businesses and optimising their data flow is our beachhead market (initial source of revenue before we get to comprehensive models).
  3. Aligning human activities – if you have a mega AI model that understands nature deeply, but not using it – it’s a problem. We’ll be actively engaged with businesses operationalising our models and tools. Always focusing on transparency!
  4. Data fragmentation and accessibility – hindering 1-3 above. We need to work on it to unlock the best models.
  5. Data wrestling for ecologists – hindering 1-3 above. This is aligned with our mission and is our initial market (doing heavy data lifting for ecologists).

To drive our mission forward:

  • We focus on foundation models for biodiversity. We bring existing cutting-edge AI and data tools and apply them to biodiversity, building a digital nervous system for the planet with the AI brain that deeply understands nature (our North Star).
  • To do that, we need a lot of biodiversity data. We will focus on unifying biodiversity data (which is currently fragmented and not easily accessible) through partnerships, providing B2B services (exchanging data/money for services) and, in parallel, building a horizontal open-data platform and a marketplace for biodiversity data (targeting different user incentives). If someone has a lot of data, we’d happily join forces and focus on modelling (our main objective). See the “getting the data” chapter for more info.
  • Building a horizontal data platform and gathering data takes time and effort. A marketplace alone might not take off quickly enough and be profitable. Businesses in our verticals might not need simple AI models (it takes data to get to comprehensive models). We need a parallel source of revenue.
  • That’s OK! In this case, we are falling back on solving business needs (for each vertical) around data management and optimising processes by building tools and services (see more in the “Product” chapter). This aligns with our mission and contributes towards solving multiple key problems. Also, we will be building tools and infra for training models anyway. We just need to keep in mind our “North Star” and not over-fit into the tooling only.
  • All the generalisable building blocks (tools and models) for biodiversity (from what we do for businesses) will be open-sourced and made available in our horizontal platform, creating more traction. This data platform (or one cloud for biodiversity) will empower biodiversity researchers with transparent, open-source tools and models.

It’s very challenging to pull this off. This seems to be the best shot at how we mitigate risks and create a sustainable business model that helps biodiversity researchers from academia and small NGOs to large corporations protect our planet better!