Data and I/O
Open, stream, subset, convert, publish, and register subsurface data while preserving source identity, lineage, and lifecycle state.
The situation
Billion-dollar decisions are made from incomplete maps of what lies underground.
Energy, carbon storage, mining, water, and infrastructure teams make enormous decisions from incomplete pictures of the earth. Foundation is a controlled software environment for that work, where experts and AI work from the same live knowledge model of the subsurface: its data, its assumptions, its history, and the evidence behind every decision.
Foundation provides the technical path from subsurface data access to accepted scientific output: data management, visualization, rock physics, seismic analysis, prestack processing, machine learning, interpretation, workflow execution, and governed AI.
AI can prepare, check, and propose. Experts decide.
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Private build, selected partners
What Foundation provides
A complete governed platform for AI-native subsurface work.
Foundation brings together data access, scientific analysis, machine learning, visualization, interpretation, workflow execution, governed AI, and customer applications in one live technical context and one governed execution model. One portfolio, one workflow state, one technical evidence model.
Interpretation and science
Run rock physics, seismic analysis, prestack conditioning, well ties, AVO or AVA, attributes, horizon analysis, 4D checks, and scientific QC inside the governed workflow.
Models and intelligence
Train and execute seismic ML, run governed inference, search for comparable patterns and analogs, and return model results to interpretation.
Visualization and workbenches
Work in linked charts, maps, crossplots, seismic volumes, surfaces, wells, faults, selections, and synchronized workbench context.
Workflow and execution
Maintain technical state, resolve valid next actions, route approved operations, sequence dependencies, pause, resume, branch, replay, and preserve the execution record.
APIs and customer applications
Expose platform capability through public APIs, signed extensions, customer applications, workflow launch, context retrieval, result publication, and evidence access.
The problem
This work is too important for the blind application of AI and too heavy to keep doing by hand.
Mapping the subsurface, everything beneath the ground we drill, mine, and build into, means moving mountains of measurement data, running physics-heavy computations, and making expert judgment calls with enormous financial and safety consequences. Much of the software behind this work still reflects an older world: isolated desktop tools, files passed between systems, and experts holding the workflow together by hand.
AI could take real weight off these teams. But today’s AI tools mostly sit beside the work. They can summarize a project or answer questions about it. They can’t safely do much of the work itself, because they can’t see what the experts see.
They also can’t bring the organization’s accumulated knowledge to the right moment: previous wells, older studies, quality-control notes, analog fields, standard methods, past decisions, and the reasons those decisions were made. That knowledge exists, but it is usually scattered across projects, documents, files, systems, and people’s heads.
- Which data can be trusted, and which data is incomplete, suspect, or out of date
- Where the work stands, what’s finished, what’s blocked, and what comes next
- What similar work already taught the organization, and which lessons apply here
- Why the current picture looks the way it does, and what the evidence supports
Foundation gives AI the technical context required to participate usefully in the work, while keeping experts in control of the decision.
The value
More trusted decisions from the same expert team.
Subsurface experts are expensive, scarce, and overloaded. Too much of their time goes into work that is not judgment: moving data, checking files, re-running steps, searching for prior knowledge, and documenting decisions after the fact.
Foundation lets AI absorb more of that load safely. The same team can evaluate more prospects, test more scenarios, and move faster without accepting the two risks that currently block AI adoption: an untraceable mistake in a high-value decision, or a workflow held hostage to a model vendor.
The value is not more AI features. It is faster technical progress without losing control of the evidence, the workflow, or the decision record.
In one line: more high-stakes subsurface decisions, made faster, with an evidence trail you can defend and an AI capability you own.
What Foundation does
One workspace for data, experts, science, and AI.
Native Foundation products perform the technical work. Data access, scientific analysis, visualization, machine learning, workflow execution, and governed AI operate through one live technical context, and each output becomes a governed input to the next technical step.
Foundation turns subsurface knowledge into a live, governed knowledge model: data, interpretations, assumptions, checks, approvals, decisions, and allowed actions are connected in one workspace, not scattered across loose files, systems, and people’s heads. Teams load data, inspect it, run analysis, test assumptions, prepare interpretations, and record the reasoning behind every decision.
One live knowledge model.
Foundation connects the real objects of subsurface work: surveys, wells, volumes, horizons, faults, interpretations, tasks, analogs, assumptions, and decisions. Experts explore the subsurface in fast, high-fidelity 3D views, and the AI works from the same operational context used by the technical team.
Scientific checks are built in.
Established scientific and physics-based methods run inside the platform, so AI proposals are checked against the same methods experts rely on.
People approve changes.
AI participates through governed actions, such as loading data, flagging suspect inputs, preparing an interpretation, running a check, and retrieving relevant prior work. Those actions follow the same permissions, validation, and approval rules as human work. Every action, human or AI, is logged with its supporting record.
Yours to build on.
Your team can build its own tools, workflows, and views on the platform, all inheriting the same safeguards.
Product surface
Native capability across the full subsurface workflow.
Data fabric
Read in place, convert when needed, preserve source identity, and track every lifecycle transition.
Scientific engines
Rock physics, seismic analysis, prestack conditioning, attributes, well ties, validation, and technical QC.
ML and seismic intelligence
Training, inference, analog search, similarity, model export, interpreter feedback, and model provenance.
Visualization and workbenches
High-fidelity 3D, charts, maps, crossplots, volumes, wells, surfaces, selections, and synchronized context.
Stateful workflow execution
Valid next actions, dependencies, branches, replay, workflow identity, provenance, and accepted state.
Customer build surface
Public APIs, signed extensions, customer applications, enterprise automation, and governed integrations.
Why it matters
Use any model. Own the intelligence.
AI vendors change their models, prices, quotas, and policies whenever they choose. Industrial and scientific work must produce the same answer next year that it produced this year, for partners, regulators, and sometimes courts.
Foundation keeps the things that matter, including workflow logic, permissions, accumulated knowledge, project history, and the technical record, inside your environment and under your control. Language models plug in as interchangeable tools. The platform, not any single model, is the load-bearing system.
Foundation is designed to work with local, open-source, specialized, and commercial models. Many useful AI tasks can run on ordinary workstations, close to the expert and close to the data. Large commercial models can be used where they add value, but they are never a mandatory dependency. Swap a model out, and your workflows, records, and results stay intact.
Your AI strategy should become an asset, not another dependency.
Why this is different
- AI works inside the subsurface knowledge model.
- Recommendations come with evidence and confidence.
- Experts approve changes before the technical record moves.
- Models are interchangeable; the workflow record remains intact.
- Your workflows and knowledge stay under your control.
- Your team can extend the platform without breaking the safeguards.
For digital teams
A development layer for governed subsurface applications.
Large organizations build dozens of internal tools around subsurface data, including loaders, quality dashboards, screening workflows, and one-off visualizations. Each one reinvents data access, 3D rendering, permissions, and auditability from scratch. Those tools are expensive to build, hard to govern, and difficult to keep consistent.
Foundation is also a development layer for your digital team. Developers build directly on the live subsurface knowledge model, the visualization engine, and the governed action layer, so they can ship subsurface applications in weeks, and every one of them inherits governance, provenance, and AI capability from the platform.
Foundation exposes a contract-first API surface for customer applications, workflow launch, context retrieval, result publication, evidence access, and enterprise automation. Customer tools enter the same authorization, validation, execution, and audit path as native workbench actions.
Tools,
specialized utilities shaped around your own operating practices.
Workflows,
encoded methods that do not have to wait for a vendor roadmap.
Views,
project-specific ways to inspect data, evidence, assumptions, and interpretation state.
Applications,
full internal products, with the technical record traveling with everything your team builds.
The experts are why Foundation is credible. Your developers are why it scales.
Where it runs
Close to the expert. As big as the job.
Expert workstation
Interactive interpretation, QC, visualization, local scientific execution, and low-latency AI assistance stay close to the person making technical judgements.
Managed services
Repeatable processing, retrieval, model serving, workflow coordination, scheduled execution, caching, provenance, and centralized audit run reliably.
Private or public cloud
Elastic scientific workloads, enterprise-scale data access, approved model routes, regional studies, and shared application services scale beyond one workstation.
High-performance computing
Large batch workflows, regional processing, simulation, ensemble runs, and compute-intensive scientific execution retain workflow identity and evidence.
Customer systems
Existing interpretation platforms, OSDU or PPDM environments, archives, data rooms, workflow engines, and internal applications participate as governed sources, targets, endpoints, or workflow participants.
Architecture message
A governed subsurface product platform.
Foundation is a governed subsurface product platform where data, science, visualization, workflow execution, AI, and customer applications operate against one live technical record.
Private preview
Built with a small number of technical partners.
We’re building Foundation with partners who want AI to participate safely in technical subsurface work. Ideal partners are teams that need to connect existing subsurface data, run scientific workflows, preserve evidence, apply AI under governance, and extend the platform through internal tools or enterprise systems.
Good fit if you are working on:
- multi-vintage seismic and well projects
- repeatable interpretation or processing workflows
- AI or ML workflows tied to evidence
- internal subsurface applications
- OSDU, PPDM, cloud, HPC, or governed AI modernization