Ascendion delivered an AI-led solution that digitized and automated Geotherm’s end-to-end soil testing workflow, while embedding intelligence through predictive modeling.
We developed two predictive models using 40 years of soil records: one for soil type classification, another for Moisture & Thermal Resistivity prediction, leveraging location and radius parameters. Built a robust data extraction engine to ingest and structure historical reports into a centralized SQL database. Integrated OCR-powered form processing to automate data capture from handwritten COC submissions, eliminating manual entry. Deployed GeoXplore Maps, an LLM-enabled module to visually navigate historical soil insights and run location-specific predictions.
Ascendion enabled customer self-service access via a secure web portal with real-time project views, reducing email dependencies. Architected and executed the entire platform within a secure Azure Cloud environment with scalable data pipelines and authentication. AAVA™ Agents accelerated engineering tasks such as user story creation, reverse engineering, code/ development, documentation, and test generation.
This GenAI powered solution transformed the client’s process into a predictive, efficient, and customer-friendly system – setting the foundation for digital scale.
This initiative marked a step-change in how the client operates – embedding AI at the core of testing operations for long-term efficiency and experience gains.
Case studies
Case studies
Case studies
Case studies
Case studies
Case studies
Case studies
Case studies
Case studies
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