BigGeo puts geophysical survey data, including seismic, gravity, and magnetic layers, into a single spatial environment where interpretation is instant and drilling targets become defensible. For the first time, your exploration team can cross-reference subsurface anomalies against surface context, land tenure, and infrastructure without waiting on a GIS specialist.

Most data vendors sell you a national license to millions of records you will never contact. BigGeo works differently.You tell us where you sell, and we cut you exactly that geographic slice of the dataset. A single city.
A cluster of ZIP codes. A metro area. A county. Whatever matches your territory. The result is a lean, CRM-ready file containing only the companies in the markets you actually work, delivered at a fraction of the cost of a full national license.

Geophysical practitioners are sitting on high-value subsurface data that is almost impossible to act on quickly. Seismic lines, gravity grids, and magnetic anomaly maps live in separate formats, separate software, and separate workflows. By the time everything is stitched together and spatially contextualized, the interpretation window has closed or the capital decision has already been made without you.
Seismic data is spatially indexed and queryable at the line or grid level, so you can immediately cross-reference subsurface structure with surface features, infrastructure corridors, and land access constraints without leaving the platform.

Gravity and magnetic field outputs are co-registered with seismic layers, enabling composite anomaly interpretation that would previously require dedicated processing software and a specialist to run it.

Interpreted deposit extents are stored as spatial objects, not static images, so exploration teams can query boundaries, calculate areas, and rank targets by size and access without a separate mapping workflow.

All survey methods feed into a single spatial environment in DataLab, so geologists, geophysicists, and engineers are always working from the same interpreted picture rather than reconciling outputs from three different software packages.

BigGeo AI is the AI access point to governed spatial data and it works directly inside ChatGPT and Claude today. Instead of queuing a data request or opening three pieces of software, an exploration practitioner can ask a plain language question about any survey area and get a spatially grounded answer in seconds, backed by real data, not training-data approximations. The interpretation work that used to take a GIS analyst a day now happens in the time it takes to type a question.
Yes. Once you bring your own survey data into DataLab, it sits on the same DGGS spatial grid as every dataset in the platform, which means combining your proprietary results with this layer is a query, not a project. You control what is shared, what is private, and what is published through Vault governance.
Interpretation software is built for signal processing, not spatial decision-making. The gap this fills is the moment after interpretation, when you need to rank targets against surface access, environmental buffers, infrastructure proximity, and land tenure in a single spatial environment. That cross-referencing step is where exploration programs lose the most time today.
Refresh cadence and coverage extent are dataset-specific and depend on the source provider. The most accurate answer for your target geography is available when you speak with the team. What does not change is the platform behavior: when new data arrives, it lands indexed and query-ready without requiring you to rebuild any workflow.
Access is through the BigGeo platform, which includes the DataLab workspace for analysis, DataScape for visualization, and API access for teams that want to pull governed spatial outputs into existing pipelines. You do not need to replace your interpretation tools. BigGeo sits at the layer where spatial context is added and cross-dataset queries are run, complementing what you already have.
The fastest path is to request a sample for your specific area of interest. The team will show you what coverage exists, how it aligns with your current survey program, and what it looks like combined with any other spatial layers relevant to your evaluation. A 30-minute call is enough to know whether this accelerates your next exploration cycle.