p:IGI+ makes importing, filtering, exploring and visualising environmental data simple. Integrating advanced tools, you can quickly provide consistent, reproducible interpretations.
Equations are a key part of the IGI software family. Here we explain how they work...
Product Owner
Version 2.3 of p:IGI+ and Metis introduce a number of new features including enhanced support for auto-artefacts, uncertainty, graphs, maps and more ...
Managing Director​ & Data Scientist
Improved artefact management is a key update delivered in v2. 3. Auto-artefacts cover the majority of artefacts including graphs, palettes, maps, pages, rule sets, dynamic sample sets and statistics. In the new release, existing autographs have been reviewed and updated, and a range of new auto-artefact templates added.
Senior Geochemist/Basin Modeller
Explore data efficiently through predefined, interactive graphs and other views.
Follow a data-driven approach, using integrated data science methods, to identify relationships in data and discover trends and outliers.
Explore the spatio-temporal context of your data, combining statistics, graphs and filtering.
Efficiently import, quality control, edit, gap-fill and collocate your data to integrate what you have measured.​
Increase productivity using a product customised to the environmental monitoring domain. Organise data effectively, especially when twinned with IGI’s ‘Metis’ centralised geoscience database.​
High quality output aids the delivery of results to key stakeholders. p:IGI+ promotes consistency that drives fast comparisons between different datasets, locations and times.
Base decisions on predefined data views based on publications, including detailed scientific information from lab analyses and bulk sensors data.
Graphs, palettes, maps and other data views assist users to delve deeply into the data, especially when coupled with interactive selection of points.
p:IGI-Enviro is rapidly evolving and integrates directly with Metis, our data management solution for specimen and sample data, and our Machine Learning tools. We are always open to opportunities for collaboration and are excited about the opportunities to extend our spatial and temporal analysis tools.
