Industry collaboration / Serpentinite Labs
Geothermal energy: geoscience data and AI collaboration
Geothermal energy is one of our priority areas for collaboration. We are interested in helping teams organize geological observations and supporting datasets so that their interpretation can be reviewed and reused.
Bring the geological evidence together
A potential workflow could connect field descriptions, structural observations, maps and project documents through consistent identifiers. The initial question is what the team needs to decide and which records support that decision, rather than how much data an AI system can ingest.
Maintain the distinction between evidence and potential
Geological observations alone do not establish the temperature, permeability or performance of a geothermal reservoir. Proposed AI outputs should identify sources, assumptions and gaps and remain subject to specialist review.
What we offer today
G-Spyke is an app for stratigraphic logging, not a geothermal resource assessment or reservoir modelling system. We do not yet have a dedicated geothermal product. We are seeking partners to define and evaluate useful software and agentic AI workflows.
Start with a reviewable pilot
A partner can bring a clearly scoped data-organization or technical-review problem, an authorized sample and an expected output. Together we can define evaluation criteria such as data completeness, source traceability and time spent checking the result.