Subatix delivers production‑grade AI systems that improve operational excellence for non‑ferrous metal and mining sites. Their platform, DataBridge, ingests raw, inconsistent plant data and reconstructs a reliable operating picture without requiring a clean data lake, enabling faster root‑cause analysis, performance management, and equipment downtime reduction. By combining consulting expertise with full‑stack AI development, Subatix helps mining operators capture additional EBITDA and modernize assets.
Funding
Funding not disclosed
Founders
Product
Problem
Non‑ferrous metal and mining plants generate large volumes of raw operational data that are often inconsistently named, stored in disparate systems, and lack a clean data lake, making root‑cause analysis, performance management, and continuous improvement slow and error‑prone.
Solution
Subatix offers the DataBridge platform, an AI‑driven intelligence layer that ingests raw exports from existing historians, LIMS, SAP, or Maximo systems and reconciles inconsistent naming and weak failure coding to reconstruct a reliable operating picture. The platform runs in‑plant, providing real‑time diagnostics, faster root‑cause analysis, and performance management without requiring data lake migration. Built on extensive consulting experience and full‑stack development, DataBridge supports ongoing monitoring, recalibration, and the addition of bespoke modules to evolve with the site’s needs. Operators can use the system as a control‑tower workspace to identify downtime reduction opportunities and capture additional EBITDA during ramp‑ups or modernization projects.
Target Audience
Primary customers are operations and engineering teams at non‑ferrous metal mines and refining facilities seeking to improve equipment uptime and financial performance.
Features
- Automatic ingestion and normalization of raw plant data from heterogeneous sources (historian, LIMS, ERP, asset management)
- AI‑based reconstruction of operating states despite inconsistent naming and incomplete failure codes
- Real‑time diagnostic dashboards for equipment downtime, root‑cause analysis, and performance tracking
- Continuous monitoring with automated recalibration and iterative improvement loops
- Extensible architecture allowing bespoke modules and custom analytics to be added on demand
- Non‑intrusive integration that layers on top of existing systems without replacing them