Context
Global biodiversity loss threatens ecosystem stability, yet conservation efforts lack real-time monitoring tools. Traditional field methods are expensive, slow, and limited in scope. We saw an opportunity to combine remote sensing (bioacoustics, satellite & flown instruments, and more) with machine learning to give conservationists and land users actionable data at scale.
Habitats.ai emerged from Mach49's Portfolio T venture studio, where I partnered with technical co-founders to build a biodiversity monitoring platform from zero.
My Role
As co-founder and CX Principal, I led customer development, product strategy, and go-to-market positioning. My work spanned:
- Customer discovery with 40+ conservation experts across three continents
- Product definition and roadmap prioritization
- Ecosystem partnership development with hardware manufacturers
- Pitch deck development and investor conversations
- Brand positioning and early marketing strategy
Approach
Customer-First Discovery
Rather than building technology in search of a problem, we spent months in conversation & discovery with field researchers, conservation NGOs, and government agency workers.
So I continued to conduct structured interviews, rode along on field monitoring trips, and mapped existing workflows to understand where our technology could create genuine value. A “quick” trip to the Brazilian Amazon revealed many of the real-world challenges for hardware in the world's most biodiverse ecosystems—deployment, moisture, battery life, data/memory card retrieval and more presented as significant challenges.
Rapid Prototyping
We quickly built an MVP that visualized species interconnections from a partner ecologist's field study for a warehouse expansion project. Leveraging GBIF data, this interactive view of species identified from a single site revealed the complexity of “everyday” landscapes, not just biodiversity hotspots like the Amazon.
Strategic Positioning
Conservation technology is crowded with solutions. I positioned Habitats.ai not as another monitoring tool, but as the "operating system for biodiversity data" - emphasizing our API-first approach that integrated with amazing existing conservation databases like GBIF and the IUCN Red List.
Impact
- Partnership Development: Evaluated pilot engagements with major conservation organizations in Brazil and Saudi Arabia.
- Technical Validation: Tested and refined MVP product scope
- Fundraising: Led development of pitch materials yielding $3.5mm seed funding approval
- Market Learning: Generated insights that informed product roadmap for 12+ months
The venture taught me how to balance technical ambition with market reality, and reinforced that successful climate tech requires deep domain expertise combined with rigorous customer development.
What I Learned
Building in the conservation space requires patience. Budget cycles are long, procurement processes are complex, and stakeholders are (rightfully) cautious about unproven technology. Success requires building trust through small wins, not grand promises.
The most valuable skill I developed: knowing when to pivot vs. when to persist. We changed our go-to-market strategy significantly based on customer feedback, but never wavered on our core technical approach.