Solutions

Decision systems for industrial and built-world operations.

Duta Analytics designs practical analytics solutions for organizations that need trusted operational visibility, spatial context, and AI-assisted decision support across physical assets, factories, and infrastructure networks.

Solution CoverageManufacturing, GIS, digital twin, and operational intelligence in one implementation path.
Primary users
Operations, engineering, management, planning
Data domains
Production, assets, quality, spatial, maintenance
Delivery model
Custom dashboards, analytics workflows, platform modules

Manufacturing SaaS

Factory Visibility

Unify production, quality, downtime, and maintenance data into one operational dashboard.

GIS Services

Spatial Analysis

Map assets, service areas, site risks, and operational coverage using GIS-ready data layers.

AI-Assisted Analytics

Decision Intelligence

Turn live operational signals into prioritized alerts, performance narratives, and recommended actions.

Digital Twin

Industrial Digital Twin

Model sites, assets, process flows, and performance signals for planning and operational review.

Operating Problems

Built for teams managing complex physical operations.

Operational data is fragmented across spreadsheets, machines, ERP exports, site reports, and ad hoc dashboards.

Leadership needs trusted visibility across plants, assets, projects, or service territories without adding reporting overhead.

Engineering, operations, and management teams need a common language for performance, risk, and intervention priority.

Spatial context is missing from industrial decisions that depend on location, coverage, infrastructure, and field conditions.

Solution Areas

Each solution expands from visibility into action.

Focused analytics programs for turning factory signals, spatial data, asset models, and operational context into clearer decisions across the organization.

Manufacturing SaaS

Factory Visibility

A unified operational layer for production, quality, downtime, maintenance, and leadership reporting.
  • Line performance and OEE
  • Downtime and maintenance signals
  • Quality variance and rework
  • Shift, asset, and plant-level reporting
Factories gain a reliable single view of operational performance without waiting for manual reporting cycles.

GIS Services

Spatial Analysis

Location intelligence for assets, service coverage, site risk, infrastructure planning, and built-world decision support.
  • Asset and site mapping
  • Service-area and catchment analysis
  • Risk and constraint layers
  • Field-ready spatial data workflows
Teams can compare operational decisions against location, infrastructure, and coverage context.

AI-Assisted Analytics

Decision Intelligence

Analytical workflows that convert live signals, historical patterns, and domain rules into prioritized action.
  • Exception monitoring
  • Performance narratives
  • Root-cause indicators
  • Recommended next actions
Leaders move from passive dashboards to guided operational review and faster escalation.

Digital Twin

Industrial Digital Twin

A structured operating model of sites, assets, process flows, and performance signals for planning and review.
  • Asset and process models
  • Signal relationships
  • Scenario comparison
  • Operational simulation readiness
Industrial teams can evaluate change, risk, and performance through a shared model of the operation.

Engagement Structure

From operational question to deployed decision workflow.

01

Define the operating question

Clarify the decisions, stakeholders, data sources, and reporting cadence that the solution must support.

02

Connect and structure data

Prepare production, spatial, asset, maintenance, quality, and business datasets into a reliable analytics model.

03

Deploy decision workflows

Deliver dashboards, alerts, review views, and analytical narratives that fit daily operational routines.

04

Improve with evidence

Iterate using adoption, data quality, operational feedback, and measurable improvement indicators.