Manages scientific and measurement data end-to-end — upstream, midstream, downstream, geothermal, and power & renewables. Cloud-agnostic. OSDU-aligned. Partner-neutral.
Smart ingestion & subsurface data management
Generative AI-driven source-to-target data mapping
AI-enabled Scientific Data Foundation
Domain agents & agentic workflows
Geospatial & scientific visualisation
Subsurface & energy workflow integration
Generic platforms handle rows and columns. PIEScale understands wells, seismic volumes, reservoir grids, DTS fiber, and what they mean to each other.
OSDU, PPDM, PODS, Energistics, WITSML, PRODML, RESQML, SEG-Y, LAS, DLIS, LIS, plus custom parsers. Headers scanned, validated, and quality-scored before ingestion.
APIs and MCP protocols connect Petrel, Decision Space, and other applications to one shared foundation — minimising duplication across the asset lifecycle.
309 wells in 3 hours. 2.9 TB seismic in 6 hours. Hart Energy Technology Showcase 2024 — not a proof of concept.
API for programmatic access, MCP for AI assistants, A2A for multi-agent workflows — any integration pattern your architecture requires.
Each component purpose-built for scientific and industrial data — no generic connectors, no adapters, no approximations.
Connects to every scientific source and maps data to target schemas with generative AI — eliminating the hand-coded work that drags migrations out for years.
The governed data lake built for scientific and industrial datasets — open table formats, entitlement-aware MCP servers, five-layer security from day one.
A low-code framework for domain-specialist agents, each scoped to one discipline. A Supervisor Agent routes queries across five categories, drawing from governed PIELake data via MCP.
Context-triggered visual widgets that wrap any AI assistant, turning text-only chat into a scientific workbench.
Connects subsurface and energy workflows into one orchestrated platform — integrating existing enterprise tools without replacing them, then exposing those workflows to agents and applications.
Not a policy document — a structural model enforced on every query and every access. Governance by architecture, not intention.
Identity provider integration — every session verified before data is reached
RBAC checked per request — not per login, per query
Which services can talk to which — scoped and enforced at the platform layer
Cloud-level access control independent of application permissions
Record-level ACLs — who sees which well, which basin, which dataset
Audit trails and lineage generated automatically — not reconstructed before every compliance deadline.
Wells, seismic, fiber-optic sensing, and reservoir grids all feed a single unified reservoir model — alongside operational sensor data from OSI PI and AVEVA Data Hub.
Extendable to new data types and use cases without re-architecting the platform.
Petrabytes connected the Fledge edge computing stack to real-time cloud data via Kafka and Delta Lake, streaming clean data into AVEVA Data Hub through the ADH API. Built with Databricks and Shell, contributed back to OSDU as the Real-Time Streaming Service standard. Presented at AVEVA World 2023.
Patented technology for managing and visualising high-volume oilfield, wellbore, and reservoir monitoring data — including distributed fiber-optic sensing (temperature, pressure, Bragg gradient, acoustic, strain) — without down-sampling.
Patented 3D visualisation and management for reservoir monitoring datasets — the IP foundation under PIEView's visualisation layer.
PIEScale runs where your data lives — native integration with ADME, EDI, Databricks, and all major cloud providers. No forced migration before value appears.
A 30-minute discovery call grounded in your actual data — not a generic product demo.