PHYLO is an AI‑driven platform that converts environmental DNA (eDNA) samples into actionable species lists, providing a molecular intelligence layer for watershed, fisheries, and habitat managers. The system delivers a queryable view of biodiversity—identifying presence, abundance, relationships, and temporal changes—through a multi‑source pipeline and a curated corpus. PHYLO runs on Google Cloud with NVIDIA Inception acceleration and has been validated by experts at the eDNA Collaborative and Conservation X Labs.
Funding
Funding not disclosed
Founders
Product
Problem
Environmental DNA (eDNA) sampling generates raw species lists but does not provide the contextual information needed for watershed, fisheries, and habitat managers to make informed conservation decisions. Without integrated analysis, users must manually interpret abundance, relationships, and temporal trends, which is time‑consuming and prone to error.
Solution
Phylo offers an AI‑driven platform that converts raw eDNA data into a queryable molecular intelligence layer. The system aggregates multi‑source pipelines on Google Cloud, accelerated by NVIDIA hardware, to produce standardized outputs describing species presence, relative abundance, ecological relationships, and changes over time. Results are validated by domain experts and presented through an interface that supports ad‑hoc queries and integration with existing workflows. By delivering actionable insights rather than just raw lists, Phylo enables managers to prioritize actions, monitor ecosystem health, and assess the impact of interventions more efficiently.
Target Audience
Primary customers are watershed, fisheries, and habitat managers in government agencies, conservation NGOs, and commercial environmental consulting firms who rely on eDNA data for ecosystem monitoring and decision‑making.
Features
- End‑to‑end cloud pipeline that ingests raw eDNA sequences and outputs structured species intelligence
- NVIDIA‑accelerated AI models that infer abundance, co‑occurrence networks, and temporal dynamics
- Queryable database allowing users to filter by species, region, time period, or ecological metric
- Expert‑validated results ensuring scientific credibility for management decisions
- Integration with Google Cloud services for scalable processing of large sample volumes
- Ongoing roadmap includes standardized scoring to harmonize results across studies