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BoreLog AI is an intelligent geotechnical data digitization platform designed to convert historical borehole logs, test pit records, CPT data, laboratory reports, and geological documents into structured, searchable, and analysis-ready digital datasets.
Powered by advanced Optical Character Recognition (OCR), document understanding AI, geological intelligence, and automated quality assurance, BoreLog AI eliminates the need for manual data entry while preserving valuable subsurface knowledge that often remains locked inside paper records and scanned PDFs.
The platform transforms decades of geotechnical information into standardized digital assets that can be integrated into GIS systems, ground models, geotechnical databases, and engineering workflows.
Across the geotechnical and engineering industry, vast amounts of valuable subsurface information remain trapped in paper archives, scanned reports, handwritten borehole logs, and legacy document repositories.
Common challenges include:
As organizations accumulate decades of project data, extracting value from legacy information becomes increasingly difficult.
BoreLog AI automates the digitization and interpretation of geotechnical records using advanced document intelligence and geological knowledge.
The platform reads scanned borehole logs, handwritten field records, test pit logs, CPT data, driller logs, laboratory reports, and geological maps. It automatically identifies borehole structures, extracts geological information, validates data quality, and converts the results into structured digital formats ready for engineering analysis.
By transforming historical records into searchable geotechnical intelligence, BoreLog AI enables organizations to unlock previously inaccessible knowledge, improve project planning, and maximize the value of existing data assets.
Convert scanned borehole logs and field records into structured digital datasets without manual data entry.
Extract information from printed documents, handwritten notes, scanned PDFs, and historical records.
Automatically identify and capture lithology, stratigraphy, soil descriptions, rock descriptions, and groundwater information.
Extract Standard Penetration Test (SPT) results, core recovery data, RQD values, sample information, and engineering properties.
Recognize borehole layouts, depth intervals, geological symbols, and tabular formats across multiple logging standards.
Validate extracted information using geological rules, classification systems, and consistency checks.
Convert extracted information into structured formats suitable for geotechnical databases and engineering software.
Enable seamless integration with GIS platforms, ground modelling software, and geotechnical information systems.
Preserve decades of historical geotechnical knowledge in a secure, searchable digital repository.
Search thousands of historical boreholes and geological records instantly using natural language or structured queries.
Users upload scanned PDFs, borehole logs, test pit logs, CPT records, laboratory reports, geological maps, and field documentation.
The system applies OCR, handwriting recognition, table extraction, symbol detection, and geological layout recognition to understand document content.
BoreLog AI identifies and extracts key geotechnical information including borehole IDs, coordinates, depths, lithology, groundwater observations, laboratory references, and subsurface descriptions.
Structured datasets are generated and exported into industry-standard formats ready for further analysis and integration.
Processes scanned reports, handwritten logs, engineering tables, symbols, and geological records using advanced AI-powered document interpretation.
Extracts and structures critical subsurface information including lithology, stratigraphy, groundwater conditions, SPT data, RQD values, and sample records.
Applies geological classification systems, soil and rock terminology, stratigraphic relationships, and engineering geology principles.
Performs automated consistency checks, depth validation, classification verification, and data quality assessments.
Stores digitized information within a searchable and reusable geotechnical knowledge framework.
Many organizations possess decades of valuable subsurface information, yet most of this knowledge remains inaccessible because it exists only within static reports and scanned documents.
BoreLog AI unlocks this information by transforming historical records into structured digital intelligence that can support future projects, reduce investigation costs, improve risk assessments, and enhance decision-making.
Instead of repeatedly collecting data that already exists, organizations can leverage their historical knowledge to gain a competitive advantage.
BoreLog AI is ideal for:
Whether managing thousands of historical borehole records or building enterprise geotechnical databases, BoreLog AI enables organizations to digitize, preserve, and maximize the value of their subsurface knowledge.
BoreLog AI is a product of Pineuron, Melbourne, VIC, Australia.
