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Minerva Intelligence
Cognitive AI software transforming complex earth science and climate data into actionable insights.
What it does
Combines human domain expertise with large scientific datasets using a proprietary cognitive AI reasoning engine. Standardizes disorganized technical data and controlled vocabularies for cross-system interoperability. Predicts optimal mineral deposit exploration sites and provides auditable rationale for geological targets. Assesses natural hazards, wildfire risks, and climate change impacts across physical asset portfolios.
Why it works
Cognitive reasoning system delivers auditable, explainable AI outputs rather than black-box statistical predictions. Standardized taxonomy tools harmonize legacy scientific datasets across disparate geographic databases. Proprietary geological algorithms reduce exploration time and expense for mining resource operators. Expansion into climate risk analytics provides recurring subscription revenue beyond traditional mining software.
Category: AI & Automation
Team Size: 11-25
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As of 2026
AI & Automation
Revenue: $1M-$10M ARR
Cognitive AI software transforming complex earth science and climate data into actionable insights.
Overview
Minerva Intelligence (now rebranded as Aisix Solutions) is an artificial intelligence software company specializing in knowledge engineering and cognitive decision-making. Designed for earth science, mining exploration, and climate risk management, the platform combines human domain expertise with large scientific datasets. Its proprietary Reasoner technology standardizes technical information and predicts natural hazards, mineral deposits, and climate impacts with auditable explanations.
Funding status: Funded
Revenue source: Subscriptions
Customer type: B2B
Pricing: Enterprise
Tech stack: Python, C++, GIS Systems, Knowledge Graph, Semantic Web
Platform: Web
Integrations: ArcGIS, QGIS, PostgreSQL, CSV, REST API
Founder story
Founded in 2017 in Vancouver, Canada, Minerva Intelligence was established to apply cognitive AI and semantic knowledge engineering to complex earth science data. The founders recognized that geoscientists spent excessive time cleaning unstructured datasets instead of evaluating targets. In August 2023, the publicly traded company officially changed its name to Aisix Solutions Inc.
What it does
- Combines human domain expertise with large scientific datasets using a proprietary cognitive AI reasoning engine
- Standardizes disorganized technical data and controlled vocabularies for cross-system interoperability
- Predicts optimal mineral deposit exploration sites and provides auditable rationale for geological targets
- Assesses natural hazards, wildfire risks, and climate change impacts across physical asset portfolios.
Who it's for
- Mineral Exploration & Mining Companies
- Government Geological Surveys
- Environmental & Climate Risk Consultants
- Insurance & Property Asset Managers
Why it works
- Cognitive reasoning system delivers auditable, explainable AI outputs rather than black-box statistical predictions
- Standardized taxonomy tools harmonize legacy scientific datasets across disparate geographic databases
- Proprietary geological algorithms reduce exploration time and expense for mining resource operators
- Expansion into climate risk analytics provides recurring subscription revenue beyond traditional mining software.
Growth strategies
- Expanding application of core cognitive AI into climate hazard and risk management products.
- Strategic partnerships with governmental geological surveys and research institutions.
- Transitioning from project- based consulting into recurring software-as-a-service asset dashboards.
- Direct technical sales targeting tier- one mining exploration and natural resource enterprises.
Alternatives
Comparison overview
- Minerva Intelligence focuses on cognitive AI, semantic knowledge graphs, and explainable decision reasoning.
- Unlike traditional 3D geological modeling packages like Seequent, Minerva standardizes unstructured scientific taxonomies to generate explainable spatial predictions.